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黑马程序员| 陈旭阳Python6.0人工智能全套课程 全新升级（完整资料） Python人工智能实战教程 编辑点评 深入浅出，结合爬虫实战，全面掌握Python人工智能技术。 ⭐ 编辑推荐 陈旭阳老师全新升级，Python 6.0人工智能全套课程，带你从零开始，实战爬虫与AI。 ✨ 课程亮点 ✦

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黑马程序员| 陈旭阳Python6.0人工智能全套课程 全新升级（完整资料）

Python人工智能实战教程

编辑点评

深入浅出，结合爬虫实战，全面掌握Python人工智能技术。

⭐ 编辑推荐

陈旭阳老师全新升级，Python 6.0人工智能全套课程，带你从零开始，实战爬虫与AI。

✨ 课程亮点

✦Python 6.0实战教学
✦爬虫与AI技术融合
✦实战项目丰富

课程目录

04IO设计模式1 集
  • IO设计模式了解_.mp4 [213.0 MB]
03操作系统IO模型5 集
  • 3.非阻塞模式IO_.mp4 [77.2 MB]
  • 6.同步IO和异步IO_.mp4 [85.2 MB]
  • 2.阻塞模式IO_.mp4 [89.5 MB]
  • 1.IO鎿嶄綔鏈川_.mp4 [112.7 MB]
  • 4.IO澶氳矾澶嶇敤_.mp4 [130.4 MB]
02进程、线程与协程3 集
  • 4.IO密集与计算密集_.mp4 [95.3 MB]
  • 3.协程的实现方式_.mp4 [80.5 MB]
  • 1.进程与线程简单对比_.mp4 [75.2 MB]
01课程介绍1 集
  • 1.课程内容与环境介绍_.mp4 [38.3 MB]
05Python爬虫与IO库16 集
  • 19.Agent模块发送请求_.mp4 [134.6 MB]
  • 5.鍗忕▼鐨勫祵濂梍.mp4 [163.8 MB]
  • 12.Gevent鐨勭尨瀛愯ˉ涓乢.mp4 [52.6 MB]
  • 15.tornado的httpclient模块使用介绍_.mp4 [123.9 MB]
  • 4.利用线程池执行Task_.mp4 [170.6 MB]
  • 3.Asyncio事件驱动代码练习_.mp4 [204.6 MB]
  • 23.Celery模块介绍_.mp4 [85.5 MB]
  • 22.Twisted使用总结_.mp4 [73.9 MB]
  • 13.Gevent鐨勫崗绋嬫睜_.mp4 [102.4 MB]
  • 8.瀛愮嚎绋嬩腑鐨凟ventLoop_.mp4 [139.6 MB]
  • 9.Asyncio实现爬虫异步的方案_.mp4 [79.9 MB]
  • 16.Twisted模块介绍_.mp4 [89.1 MB]
  • 2.Asyncio模块介绍_.mp4 [128.3 MB]
  • 24.Celery使用(一)_.mp4 [54.0 MB]
  • 20.Twisted获取响应数据_.mp4 [124.6 MB]
  • 1.Python异步库使用介绍_.mp4 [51.7 MB]
04爬虫系统与架构方案设计实现30 集
  • 14.使用布隆过滤器进行请求过滤(二)_.mp4 [102.4 MB]
  • 16.丢失请求与失败请求的捕获(二)_.mp4 [225.2 MB]
  • 10.异步并发代码实现_.mp4 [316.7 MB]
  • 8.代码运行测试_.mp4 [247.4 MB]
  • 34.将日志发送到微信实现警报_.mp4 [242.6 MB]
  • 3.Request对象和Response对象实现_.mp4 [229.5 MB]
  • 6.主逻辑实现(一)_.mp4 [383.2 MB]
  • 29.logstash向kafka生成日志数据(一)_.mp4 [207.8 MB]
  • 12.基础策略代码实现优化_.mp4 [101.8 MB]
  • 17.丢失请求与失败请求的捕获(三)_.mp4 [187.2 MB]
  • 19.Selenium与Chrome-Headless并发下载(一)_.mp4 [243.7 MB]
  • 2.基础策略实现代码结构介绍_.mp4 [74.3 MB]
  • 32.logstash数据过滤与定向输出(一)_.mp4 [62.9 MB]
  • 1.爬虫系统架构实现与request_manager回顾_.mp4 [194.4 MB]
  • 31.logstash向kafka生成日志数据(三)_.mp4 [44.8 MB]
  • 11.异步并发代码改造优化_.mp4 [159.6 MB]
  • 23.日志收集和监控的必要性_.mp4 [116.6 MB]
  • 20.Selenium与Chrome-Headless并发下载(二)_.mp4 [177.5 MB]
  • 9.新增下载器组件实现请求发出_.mp4 [214.6 MB]
  • 30.logstash向kafka生成日志数据(二)_.mp4 [101.4 MB]
  • 5.爬虫逻辑与基类实现_.mp4 [167.1 MB]
  • 18.丢失请求与失败请求的捕获(四)_.mp4 [261.5 MB]
  • 24.日志模块的简单使用_.mp4 [150.8 MB]
  • 33.logstash数据过滤与定向输出(二)_.mp4 [84.3 MB]
  • 4.下载器对象实现_.mp4 [200.8 MB]
  • 15.丢失请求与失败请求的捕获(一)_.mp4 [242.8 MB]
  • 22.模块安装_.mp4 [264.0 MB]
  • 13.使用布隆过滤器进行请求过滤(一)_.mp4 [102.9 MB]
  • 26.Logstash的工作原理_.mp4 [215.5 MB]
  • 21.Selenium与Chrome-Headless并发下载(三)_.mp4 [346.7 MB]
01课程内容和系统环境介绍1 集
  • 1.课程内容与系统环境介绍_.mp4 [76.7 MB]
06总结1 集
  • 1.课程总结_.mp4 [130.0 MB]
05项目实战-豆瓣爬虫改造6 条
  • 1.案例-doubanbook爬虫改造(一)_.pcwlenv [66.9 MB]
  • 3.案例-doubanbook爬虫改造(三)_.pcwlenv [79.6 MB]
  • 5.案例-doubanbook爬虫改造(五)_.pcwlenv [80.2 MB]
  • 4.案例-doubanbook爬虫改造(四)_.pcwlenv [47.2 MB]
  • 2.案例-doubanbook爬虫改造(二)_.pcwlenv [66.1 MB]
  • 6.案例-doubanbook爬虫改造(六)_.pcwlenv [83.0 MB]
03爬虫系统与架构组件介绍6 集
  • 5.爬虫系统架构组件介绍(四)_.mp4 [158.3 MB]
  • 6.爬虫系统架构组件介绍(五)_.mp4 [76.5 MB]
  • 2.爬虫系统架构组件介绍(一)_.mp4 [135.1 MB]
  • 4.爬虫系统架构组件介绍(三)_.mp4 [119.2 MB]
  • 3.爬虫系统架构组件介绍(二)_.mp4 [83.9 MB]
  • 1.爬虫系统架构组件整体掌握_.mp4 [63.5 MB]
02爬虫系统与架构介绍11 集
  • 7.爬虫系统架构设计方案1优化策略(二)_.mp4 [163.7 MB]
  • 5.爬虫系统架构设计方案1内部逻辑_.mp4 [108.9 MB]
  • 4.爬虫系统架构设计方案1_.mp4 [153.0 MB]
  • 2.为什么要自行实现一个爬虫系统架构_.mp4 [158.4 MB]
  • 10.爬虫系统架构设计方案2简介_.mp4 [82.9 MB]
  • 9.爬虫系统架构设计方案1优化策略(四)_.mp4 [128.7 MB]
  • 11.爬虫系统架构介绍小结_.mp4 [43.6 MB]
  • 1.爬虫系统架构概念介绍_.mp4 [169.1 MB]
  • 8.爬虫系统架构设计方案1优化策略(三)_.mp4 [96.4 MB]
  • 3.爬虫系统架构中需要实现的主要爬虫业务_.mp4 [215.3 MB]
  • 6.爬虫系统架构设计方案1优化策略(一)_.mp4 [107.5 MB]
01课程介绍1 集
  • 1.爬虫中的请求管理课程概要_.mp4 [32.5 MB]
05断点续爬与增量抓取1 集
  • 54.利用请求管理实现断点续爬、增量抓取的思路分析_.mp4 [141.7 MB]
03队列与Python18 集
  • 14.python中持久化队列介绍_.mp4 [114.9 MB]
  • 16.基于redis实现FIFO、LIFO队列_.mp4 [131.4 MB]
  • 21.redis分布式锁实现原理_.mp4 [198.1 MB]
  • 20.redis共享资源竞争问题解决方案_.mp4 [155.5 MB]
  • 18.基于redis的优先级队列实现_.mp4 [321.7 MB]
  • 27.redis优先级队列测试与总结_.mp4 [62.3 MB]
  • 26.解决redis优先级队列中的资源竞争问题_.mp4 [230.2 MB]
  • 15.基于redis实现队列的原理_.mp4 [181.0 MB]
  • 28.请求管理整体实现方案分析_.mp4 [173.0 MB]
  • 22.redis分布式锁注意实现以及死锁_.mp4 [114.2 MB]
  • 30.请求管理模块使用测试_.mp4 [241.0 MB]
  • 24.redis分布式锁使用测试与bug调试_.mp4 [242.3 MB]
  • 25.redis分布式锁实现(补充)_.mp4 [176.3 MB]
  • 23.redis分布式锁实现_.mp4 [134.3 MB]
  • 19.redis共享资源竞争问题_.mp4 [171.5 MB]
  • 17.基于redis实现优先级队列的原理_.mp4 [203.4 MB]
  • 29.请求管理代码实现分析_.mp4 [242.4 MB]
  • 13.python中临时队列介绍_.mp4 [159.0 MB]
02请求管理简介11 集
  • 6.请求去重代码初步实现_.mp4 [181.5 MB]
  • 7.请求判断依据数据处理逻辑分析_.mp4 [290.5 MB]
  • 4.去重方案代码调用_.mp4 [24.5 MB]
  • 12.请求调度原理分析_.mp4 [127.5 MB]
  • 3.请求去重管理简介_.mp4 [57.4 MB]
  • 5.请求去重的判断依据与实现逻辑_.mp4 [2.5 MB]
  • 8.请求判断依据数据处理逻辑实现.mp4_.mp4 [308.4 MB]
  • 11.请求缓冲与调度管理分析_.mp4 [64.6 MB]
  • 2.请求管理简介_.mp4 [53.1 MB]
  • 10.请求去重模块测试(二)_.mp4 [189.3 MB]
  • 9.请求去重模块测试(一)_.mp4 [136.2 MB]
04消息队列与Python21 集
  • 49.rabbitmq中的直连交换机_.mp4 [265.2 MB]
  • 40.kafka的分区特征介绍_.mp4 [201.0 MB]
  • 45.rabbitmq工作环境搭建介绍_.mp4 [157.1 MB]
  • 43.kafka中消费者数量与topic分区数之间的关系_.mp4 [125.1 MB]
  • 35.kafka工作原理介绍(三)_.mp4 [96.1 MB]
  • 53.消息队列与请求管理实现总结_.mp4 [104.2 MB]
  • 51.rabbitmq中的扇形交换机_.mp4 [71.9 MB]
  • 42.kafka的消费者组的特征_.mp4 [72.7 MB]
  • 32.消息队列介绍_.mp4 [78.0 MB]
  • 39.Docker中利用桥接网络模式启动kafka_.mp4 [113.3 MB]
  • 47.rabbitmq中队列的特征_.mp4 [152.6 MB]
  • 33.kafka工作原理介绍(一)_.mp4 [51.3 MB]
  • 48.rabbitmq中消费者的ack确认机制_.mp4 [196.5 MB]
  • 44.rabbitmq工作原理介绍_.mp4 [216.7 MB]
  • 38.confluent-kafka-python安装与使用_.mp4 [193.8 MB]
  • 34.kafka工作原理介绍(二)_.mp4 [53.2 MB]
  • 37.利用docker-compose启动kafka_.mp4 [190.1 MB]
  • 52.rabbitmq中的首部交换机_.mp4 [100.5 MB]
  • 41.向指定的分区生产和消费数据_.mp4 [229.6 MB]
  • 36.kafka工作环境搭建介绍_.mp4 [122.5 MB]
  • 50.rabbitmq中的主题交换机_.mp4 [89.0 MB]
03HTTP、HTTPS协议与爬虫15 集
  • 14.利用Dockerfile配置安装Python环境(二)_.mp4 [67.6 MB]
  • 16.Docker中selenium与chrome爬虫开发环境搭建与使用(二)_.mp4 [114.1 MB]
  • 22.Docker中appium与android爬虫开发环境搭建与使用(四)_.mp4 [37.3 MB]
  • 11.HTTPS协议基本原理介绍_.mp4 [47.5 MB]
  • 13.利用Dockerfile配置安装Python环境(一)_.mp4 [79.4 MB]
  • 21.Docker中appium与android爬虫开发环境搭建与使用(三)_.mp4 [29.4 MB]
  • 19.Docker中appium与android爬虫开发环境搭建与使用(一)_.mp4 [70.1 MB]
  • 17.Docker中selenium与chrome爬虫开发环境搭建与使用(三)_.mp4 [135.2 MB]
  • 10.HTTP协议基本原理介绍_.mp4 [93.5 MB]
  • 24.爬虫开发环境搭建小结_.mp4 [17.6 MB]
  • 15.Docker中selenium与chrome爬虫开发环境搭建与使用(一)_.mp4 [100.0 MB]
  • 18.Docker中selenium与chrome爬虫开发环境搭建与使用(四)_.mp4 [98.2 MB]
  • 23.Docker中appium与android爬虫开发环境搭建与使用(五)_.mp4 [58.2 MB]
  • 12.Python中HTTP？HTTPS相关模块介绍_.mp4 [89.3 MB]
  • 20.Docker中appium与android爬虫开发环境搭建与使用(二)_.mp4 [100.7 MB]
04数据抓包与环境配置4 集
  • 27.利用Charles配置移动端app抓包_.mp4 [80.2 MB]
  • 25.数据抓包介绍_.mp4 [68.8 MB]
  • 26.利用Charles配置PC端web抓包_.mp4 [81.7 MB]
  • 28.数据抓包小结_.mp4 [6.4 MB]
02Python开发与Docker8 集
  • 7.配置代码自动上传与运行(二)_.mp4 [52.9 MB]
  • 9.Pycharm中docker-compose-file的配置与使用_.mp4 [37.7 MB]
  • 5.配置远程Docker的镜像作为Pycharm的python解释器_.mp4 [62.2 MB]
  • 6.配置代码自动上传与运行(一)_.mp4 [53.1 MB]
  • 3.Pycharm与Docker开发思路和原理_.mp4 [23.8 MB]
  • 2.系统环境介绍_.mp4 [27.8 MB]
  • 8.Pycharm中Dockerfile的配置与使用_.mp4 [73.6 MB]
  • 4.Pycharm中配置Docker-Daemon的连接_.mp4 [68.0 MB]
01课程介绍1 集
  • 1.Python爬虫开发环境与Docker课程介绍_.mp4 [102.1 MB]
05WebSocket协议与爬虫2 集
  • 30WebSocket客户端工具使用介绍与总结_.mp4 [84.3 MB]
  • 29.WebSocket协议介绍_.mp4 [32.5 MB]
04爬虫数据清洗1 集
  • 1.爬虫数据清洗_.mp4 [100.0 MB]
03爬虫数据存储18 集
  • 17.案例-sqlalchemy建立模型类_.mp4 [210.6 MB]
  • 9.案例-需求分析介绍_.mp4 [105.2 MB]
  • 13.案例-详情页抓取实现(一)_.mp4 [183.3 MB]
  • 7.psycopg2使用_.mp4 [112.3 MB]
  • 16.案例-将数据存入json文件_.mp4 [38.4 MB]
  • 8.PyMongo使用_.mp4 [114.0 MB]
  • 20.案例-mongoengine使用_.mp4 [71.5 MB]
  • 2.文件存储_.mp4 [118.9 MB]
  • 11.案例-列表页抓取实现_.mp4 [59.1 MB]
  • 15.案例-数据清洗_.mp4 [202.6 MB]
  • 19.案例-django-orm的使用_.mp4 [181.1 MB]
  • 18.案例-sqlalchemy实现爬虫数据存储主逻辑_.mp4 [101.1 MB]
  • 14.案例-详情页抓取实现(二)_.mp4 [163.2 MB]
  • 12.案例-列表页翻页实现_.mp4 [136.4 MB]
  • 3.数据库环境的搭建介绍_.mp4 [102.2 MB]
  • 10.案例-标签页抓取实现_.mp4 [77.0 MB]
  • 6.PyMySQL使用_.mp4 [215.2 MB]
  • 1.爬虫数据存储介绍_.mp4 [40.0 MB]
02爬虫数据解析与提取22 集
  • 17.bs4使用介绍(二)_.mp4 [56.6 MB]
  • 14.lxml模块使用介绍_.mp4 [193.4 MB]
  • 10.正则表达式规则(七)_.mp4 [179.2 MB]
  • 8.正则表达式规则(五)_.mp4 [135.5 MB]
  • 7.正则表达式规则(四)_.mp4 [161.6 MB]
  • 12.xpath规则与运用介绍_.mp4 [161.2 MB]
  • 6.正则表达式规则(三)_.mp4 [126.9 MB]
  • 4.正则表达式规则(一)_.mp4 [301.8 MB]
  • 11.正则表达式模块-re_.mp4 [168.3 MB]
  • 24.pyexecjs模块使介绍_.mp4 [51.4 MB]
  • 22.nodejs环境安装介绍_.mp4 [88.7 MB]
  • 2.爬虫数据解析与提取方案介绍_.mp4 [97.0 MB]
  • 19.jsonpath规则与运用介绍_.mp4 [91.4 MB]
  • 9.正则表达式规则(六)_.mp4 [99.7 MB]
  • 23.js2py模块使用_.mp4 [268.3 MB]
  • 21.解析规则小结_.mp4 [63.5 MB]
  • 3.正则表达式规则与运用介绍_.mp4 [95.4 MB]
  • 25.pyexecjs模块使用_.mp4 [144.0 MB]
  • 5.正则表达式规则(二)_.mp4 [35.3 MB]
  • 18.Pyquery使用介绍_.mp4 [75.1 MB]
  • 1.爬虫数据解析与提取介绍_.mp4 [213.6 MB]
  • 15.css选择器规则与运用介绍_.mp4 [45.2 MB]
01课程介绍2 集
  • 1.爬虫中的数据处理课程介绍_.mp4 [41.7 MB]
  • 2.课程涉及系统环境介绍_.mp4 [64.3 MB]
03网站反爬策略应对8 集
  • 5.ADSL拨号代理实现原理_.mp4 [47.6 MB]
  • 4.代理IP的来源_.mp4 [146.8 MB]
  • 3.代理池维护_.mp4 [97.4 MB]
  • 6.Cookie池使用_.mp4 [31.5 MB]
  • 2.UA池的使用_.mp4 [24.7 MB]
  • 7.自动化构建加密参数的方案_.mp4 [112.3 MB]
  • 1.应对反爬的基本思路_.mp4 [104.2 MB]
  • 8.自动化解决验证码的方案_.mp4 [149.2 MB]
02网站反爬策略分析3 集
  • 2.网站如何识别爬虫.flv [184.1 MB]
  • 3.网站如何惩治爬虫_.mp4 [118.1 MB]
  • 1.网站为什么反爬_.mp4 [42.5 MB]
01课程介绍1 集
  • 1.课程内容介绍_.mp4 [18.1 MB]
04总结1 集
  • 1.课程总结_.mp4 [67.5 MB]
05总结1 条
  • 17_失信人名单爬虫项目总结_.pcwlenv [34.4 MB]
03最高人民法院失信人信息爬取3 集
  • 10_最高人民法院失信人爬虫信息去重_.mp4 [46.3 MB]
  • 09_最高人民法院失信人信息爬虫_.mp4 [71.7 MB]
  • 08_最高人民法院失信人页面分析确定URL_.mp4 [70.7 MB]
01需求与开发准备3 集
  • 02_开发环境与技术选择_.mp4 [11.5 MB]
  • 01_需求_.mp4 [45.2 MB]
  • 03_创建项目与定义数据模型_.mp4 [32.7 MB]
02百度失信人信息爬取4 集
  • 07_下载器中间件_.mp4 [64.6 MB]
  • 05_百度失信人信息爬虫实现_.mp4 [92.2 MB]
  • 06_保存失信人信息_.mp4 [116.5 MB]
  • 04_百度失信人信息爬虫URL分析_.mp4 [66.3 MB]
04国家企业信用公告系统失信人信息爬取6 集
  • 12_国家企业信用公告系统爬虫_解决传递cookie问题_.mp4 [196.3 MB]
  • 13_国家企业信用公告系统爬虫_生成爬虫与跳过原有的下载器中间件_.mp4 [28.8 MB]
  • 15_国家企业信用公告系统爬虫_实现公告系统中间件_.mp4 [65.6 MB]
  • 14_国家企业信用公告系统爬虫_实现生成cookie的脚本_.mp4 [114.3 MB]
  • 11_国家企业信用公告系统爬虫_确定请求_.mp4 [104.1 MB]
  • 16_国家企业信用公告系统爬虫_完善爬虫_.mp4 [131.2 MB]
03Docker核心技术之镜像12 集
  • 6.Docker镜像管理之镜像删除_.mp4 [81.6 MB]
  • 1.Docker镜像阶段课程介绍与镜像简介_.mp4 [8.5 MB]
  • 12.Docker镜像阶段课程总结_.mp4 [2.9 MB]
  • 4.Docker镜像管理之镜像查看与下载（二）_.mp4 [17.4 MB]
  • 10.Docker镜像管理之镜像详细信息查看_.mp4 [19.5 MB]
  • 8.Docker镜像管理之镜像还原导入_.mp4 [10.8 MB]
  • 7.Docker镜像管理之镜像保存与备份_.mp4 [5.9 MB]
  • 3.Docker镜像管理之镜像查看与下载（一）_.mp4 [65.6 MB]
  • 9.Docker镜像管理之镜像重命名_.mp4 [6.3 MB]
  • 11.Docker镜像管理之镜像历史信息查看_.mp4 [13.5 MB]
  • 2.镜像管理之镜像搜索以及镜像信息_.mp4 [27.5 MB]
  • 5.Docker镜像管理之镜像查看与下载（三）_.mp4 [22.6 MB]
01Docker概览6 集
  • 3.了解Docker_.mp4 [90.4 MB]
  • 1.整体课程内容介绍_.mp4 [31.1 MB]
  • 4.Docker整体结构了解_.mp4 [12.0 MB]
  • 5.Docker底层技术了解_.mp4 [76.7 MB]
  • 6.Docker概览阶段课程总结_.mp4 [13.6 MB]
  • 2.Docker概览阶段课程简介_.mp4 [8.1 MB]
08Docker核心技术之仓库8 集
  • 1.Docker私有仓库了解_.mp4 [24.5 MB]
  • 6.具备认证的私有仓库搭建_.mp4 [82.5 MB]
  • 5.向私有仓库下载镜像_.mp4 [16.5 MB]
  • 2.了解Docker私有仓库搭建_.mp4 [30.5 MB]
  • 8.Docker仓库阶段总结_.mp4 [4.5 MB]
  • 4.向私有仓库上传镜像_.mp4 [74.8 MB]
  • 7.使用具备认证功能的私有仓库_.mp4 [32.5 MB]
  • 3.无认证的私有仓库搭建_.mp4 [124.6 MB]
04Docker核心技术之容器21 集
  • 5.了解虚拟机的生命周期_.mp4 [71.4 MB]
  • 22.Docker容器阶段课程总结_.mp4 [33.4 MB]
  • 8.Docker生命周期管理之容器创建dockerQQcreate（二）_.mp4 [61.4 MB]
  • 11.Docker生命周期管理之容器创建并启动dockerQQrun_.mp4 [97.2 MB]
  • 6.了解容器的生命周期_.mp4 [57.8 MB]
  • 7.Docker生命周期管理之容器创建dockerQQcreate（一）_.mp4 [107.6 MB]
  • 9.Docker生命周期管理之容器删除dockerQQrm_.mp4 [42.9 MB]
  • 16.Docker容器详细信息查看_.mp4 [39.9 MB]
  • 15.Docker生命周期管理之容器重启dockerQQrestart_.mp4 [9.3 MB]
  • 14.Docker生命周期管理之容器暂停_.mp4 [27.8 MB]
  • 17.Docker容器日志查看_.mp4 [66.1 MB]
  • 12.Docker生命周期管理之容器关闭dockerQQstop_.mp4 [53.6 MB]
  • 4.容器与虚拟机对比（二）_.mp4 [55.2 MB]
  • 20.Docker容器运行时执行新命令QQdockerQQexec_.mp4 [67.4 MB]
  • 13.Docker生命周期管理之容器终止dockerQQkill_.mp4 [86.3 MB]
  • 1.Docker容器阶段课程简介_.mp4 [12.9 MB]
  • 2.了解Docker容器_.mp4 [5.7 MB]
  • 18.Docker容器重命名_.mp4 [17.3 MB]
  • 19.Docker容器连接QQdockerQQattach_.mp4 [77.0 MB]
  • 10.Docker生命周期管理之容器启动dockerQQstart_.mp4 [140.2 MB]
  • 3.容器与虚拟机对比（一）_.mp4 [55.3 MB]
07Docker核心技术之数据卷12 集
  • 6.Docker数据卷管理之volume方式挂载数据卷_.mp4 [97.5 MB]
  • 1.Docker数据管理之课程简介_.mp4 [7.8 MB]
  • 10.Docker数据卷管理之volume方式数据卷的注意事项（二）_.mp4 [26.0 MB]
  • 2.Docker数据管理之数据卷简介（一）_.mp4 [26.3 MB]
  • 5.Docker数据卷管理之bind方式挂载数据卷_.mp4 [12.0 MB]
  • 12.Docker数据管理阶段总结_.mp4 [16.7 MB]
  • 3.Docker数据管理之数据卷简介（二）_.mp4 [33.9 MB]
  • 9.Docker数据卷管理之volume方式数据卷的注意事项（一）_.mp4 [8.0 MB]
  • 11.Docker数据卷管理之volume方式数据卷的注意事项（三）_.mp4 [53.5 MB]
  • 4.Docker数据卷管理之数据卷挂载方式介绍_.mp4 [35.3 MB]
  • 8.Docker数据卷管理之数据卷容器_.mp4 [23.8 MB]
  • 7.Docker数据卷管理之tmpfs方式挂载数据卷_.mp4 [33.4 MB]
10Docker核心技术之Docker-Compose27 集
  • 12.单机ELK部署之composeQQfile撰写思路_.mp4 [66.5 MB]
  • 2.DockerQQCompose工作原理介绍_.mp4 [59.4 MB]
  • 18.单机ELK部署之总结_.mp4 [43.5 MB]
  • 20.多主机ELK部署之跨主机下的composeQQfile工作原理_.mp4 [70.9 MB]
  • 17.单机ELK部署之加入kibana实现完成部署（二）_.mp4 [65.2 MB]
  • 10.部署小型wen项目之数据卷挂载_.mp4 [131.1 MB]
  • 24.多主机ELK部署之启动与调试bug（一）_.mp4 [74.5 MB]
  • 1.DockerQQCompose课程介绍_.mp4 [42.5 MB]
  • 19.多主机ELK部署之swarm介绍_.mp4 [12.8 MB]
  • 23.多主机ELK部署之改写composeQQfile_.mp4 [82.5 MB]
  • 21.多主机ELK部署之步骤分析_.mp4 [12.2 MB]
  • 25.多主机ELK部署之启动与调试bug（二）_.mp4 [157.5 MB]
  • 16.单机ELK部署之加入kibana实现完成部署（一）_.mp4 [117.1 MB]
  • 6.部署小型web项目之项目代码实现_.mp4 [39.2 MB]
  • 9.部署小型web项目之docker-compose启动_.mp4 [124.1 MB]
  • 22.多主机ELK部署之composeQQfile中deploy参数概览_.mp4 [117.3 MB]
  • 15.单机ELK部署之加入Logstash_.mp4 [34.5 MB]
  • 4.了解DockerQQComposeQQFile_.mp4 [21.1 MB]
  • 26.多主机ELK部署之总结_.mp4 [114.5 MB]
  • 14.单机ELK部署之启动elasticsearch_.mp4 [232.7 MB]
  • 3.DockerQQCompose安装_.mp4 [73.9 MB]
  • 7.部署小型web项目之Dockerfile实现_.mp4 [97.9 MB]
  • 8.部署小型web项目之docker-compose文件撰写_.mp4 [41.2 MB]
  • 27.DockerQQCompose阶段课程总结_.mp4 [3.4 MB]
  • 11.单机ELK部署之ELK介绍_.mp4 [93.9 MB]
  • 5.DockerQQComposeQQFile配置概览_.mp4 [148.5 MB]
  • 13.单机ELK部署之elasticsearch的composeQQfile撰写_.mp4 [125.0 MB]
09Docker核心技术之Dockerfile19 集
  • 5.Dockerfile构建过程的特征_.mp4 [80.0 MB]
  • 18.Dockerfile配置之其他配置_.mp4 [50.2 MB]
  • 12.Dockerfile配置之LABEL与MAINTAINER_.mp4 [41.9 MB]
  • 11.Dockerfile配置之CMD与ENTRYPOINT_.mp4 [110.6 MB]
  • 6.Docekrfile构建的镜像的特征_.mp4 [184.6 MB]
  • 16.Dockerfile配置之VOLUME_.mp4 [23.5 MB]
  • 8.Dockerfile配置说明_.mp4 [41.6 MB]
  • 9.Dockerfile配置之RUN_.mp4 [19.5 MB]
  • 15.Dockerfile配置之ADD与COPY_.mp4 [47.4 MB]
  • 10.Dockerfile配置之shell格式命令与exec格式命令区别_.mp4 [56.1 MB]
  • 2.了解Dockerfile_.mp4 [18.0 MB]
  • 4.利用Dockerfile构建镜像_.mp4 [159.7 MB]
  • 7.Dockerfile的命令与镜像层级的关系介绍_.mp4 [25.8 MB]
  • 1.Dockerfile课程介绍_.mp4 [31.8 MB]
  • 19.Dockerfile阶段总结_.mp4 [42.0 MB]
  • 13.Dockerfile配置之EXPOSE_.mp4 [35.6 MB]
  • 3.Dockerfile的撰写示范_.mp4 [8.4 MB]
  • 14.Dockerfile配置之ENV与ARG_.mp4 [60.3 MB]
  • 17.Dockerfile配置之USER和WORKDIR_.mp4 [22.4 MB]
02Docker版本与安装介绍6 集
  • 1.Docker安装与版本了解_.mp4 [5.6 MB]
  • 5.加速器配置方法_.mp4 [20.6 MB]
  • 3.Ubuntu上安装Docker_.mp4 [12.6 MB]
  • 6.Docker版本与安装阶段课程总结_.mp4 [37.1 MB]
  • 2.CentOS上安装Docker_.mp4 [20.2 MB]
  • 4.Windows、MacOS安装Docker_.mp4 [3.6 MB]
05Docker核心技术之容器与镜像7 集
  • 6.联合文件系统与Docker镜像_.mp4 [134.3 MB]
  • 1.Docker容器与镜像的关系_.mp4 [17.8 MB]
  • 8.容器与镜像阶段总结_.mp4 [35.5 MB]
  • 2.Docker容器提交-docerkQQcommit_.mp4 [11.9 MB]
  • 7.联合文件系统与容器_.mp4 [8.3 MB]
  • 4.Docker初始镜像构建-dockerQQimport_.mp4 [18.5 MB]
  • 3.Docker容器的导出-dockerQQexport_.mp4 [26.5 MB]
06Docker核心技术之网络管理21 集
  • 11.Docker网络模式之定制bridge网络_.mp4 [80.1 MB]
  • 14.Docker网络模式之Container网络模式原理_.mp4 [69.3 MB]
  • 1.Docker网络管理阶段课程简介_.mp4 [8.6 MB]
  • 3.Docker网络管理之网络查看_.mp4 [36.3 MB]
  • 9.Docker网络模式之网络模式简介_.mp4 [6.8 MB]
  • 19.Docker网络模式之overlay网络的应用场景_.mp4 [77.2 MB]
  • 7.Docker网络管理之网络使用_.mp4 [5.0 MB]
  • 21.Docker网络管理阶段总结_.mp4 [23.4 MB]
  • 18.Docker网络模式之overlay网络模式实现原理_.mp4 [67.0 MB]
  • 6.Docker网络管理之网络详细信息查看_.mp4 [5.4 MB]
  • 8.Docker网络管理之网络连接与断开_.mp4 [7.9 MB]
  • 15.Docker网络模式之none网络介绍_.mp4 [3.8 MB]
  • 4.Docker网络管理之网络创建_.mp4 [131.8 MB]
  • 13.Docker网络模式之host网络模式原理_.mp4 [82.9 MB]
  • 2.了解Docker的网络管理_.mp4 [111.9 MB]
  • 5.Docker网络管理之网络删除_.mp4 [18.2 MB]
  • 17.Docker网络模式之TCP、IP协议栈工作流程了解_.mp4 [34.9 MB]
  • 12.Docker网络模式之bridge网络的端口映射_.mp4 [147.8 MB]
  • 20.Docker网络模式之macvlan网络模式原理_.mp4 [75.8 MB]
  • 10.Docker网络模式之bridge网络原理_.mp4 [123.0 MB]
  • 16.Docker网络模式之overlay网络简介_.mp4 [46.7 MB]
02分类数据抓取3 集
  • 05_创建分类爬虫抓取数据_.mp4 [154.2 MB]
  • 06_保存分类数据_.mp4 [45.2 MB]
  • 04_确定分类信息的URL_.mp4 [20.8 MB]
01需求与实现步骤3 集
  • 02_京东全网爬虫实现步骤(1)_.mp4 [28.8 MB]
  • 01_需求与技术选择_.mp4 [30.9 MB]
  • 03_定义数据模型明确抓取的数据_.mp4 [40.8 MB]
03反爬及总结2 集
  • 17_QQ京东全网爬虫总结_.mp4 [20.9 MB]
  • 16_QQ实现下载器中间件_.mp4 [72.3 MB]
01课程介绍1 集
  • 1.爬虫中的去重处理课程介绍_.mp4 [25.7 MB]
03基于信息摘要算法的去重8 集
  • 14.优化基于mysql实现的去重过滤器_.mp4 [146.8 MB]
  • 13.实现并测试基于mysql的去重过滤器_.mp4 [421.9 MB]
  • 7.信息摘要算法介绍_.mp4 [216.3 MB]
  • 12.实现并测试基于redis中无序集合的去重过滤器_.mp4 [300.2 MB]
  • 11.测试基于python中set的去重过滤器_.mp4 [106.2 MB]
  • 10.实现基于python中set的去重过滤器_.mp4 [117.1 MB]
  • 8.信息摘要算法实现方案介绍_.mp4 [62.6 MB]
  • 9.去重过滤器基类实现_.mp4 [411.8 MB]
04基于simhash算法的去重4 集
  • 17.simhash模块使用(一)_.mp4 [146.4 MB]
  • 16.基于simhash算法的去重原理_.mp4 [89.4 MB]
  • 15.simhash算法去重方案及其应用场景介绍_.mp4 [65.3 MB]
  • 18.simhash模块使用(二)_.mp4 [251.9 MB]
02去重应用场景及其基本原理5 集
  • 5.判断依据之原始数据与原始数据特征_.mp4 [137.6 MB]
  • 2.爬虫中的去重应用场景_.mp4 [48.3 MB]
  • 6.去重容器类型介绍_.mp4 [143.5 MB]
  • 4.去重原理之去重容器_.mp4 [206.3 MB]
  • 3.去重原理之判断依据_.mp4 [172.0 MB]
05布隆过滤器原理与实现7 集
  • 24.redis版布隆过滤器实现之hash表的原理_.mp4 [68.5 MB]
  • 20.布隆过滤器实现原理_.mp4 [209.9 MB]
  • 19.布隆过滤器介绍_.mp4 [38.8 MB]
  • 23.redis版布隆过滤器实现之计算多个hash值_.mp4 [206.0 MB]
  • 22.pybloom模块介绍_.mp4 [61.0 MB]
  • 21.布隆过滤器实现原理补充_.mp4 [65.6 MB]
  • 25.redis版布隆过滤器实现之模块封装_.mp4 [311.0 MB]
4_分类管理13 集
  • 09黑马文学-分类书本列表分页查询返回数据_.mp4 [30.2 MB]
  • 05黑马文学-书籍分类列表接口设计分析_.mp4 [9.6 MB]
  • 11黑马文学-热门搜索词步骤和代码实现_.mp4 [20.0 MB]
  • 01黑马文学-课程介绍_.mp4 [5.8 MB]
  • 03黑马文学-分类列表代码实现_.mp4 [37.3 MB]
  • 12黑马文学-热门搜索词补充说明_.mp4 [7.5 MB]
  • 07黑马文学-分类书本列表获取参数_.mp4 [12.6 MB]
  • 13黑马文学-总结_.mp4 [14.9 MB]
  • 10黑马文学-分类书籍列表测试_.mp4 [8.7 MB]
  • 02黑马文学-分类列表实现步骤_.mp4 [7.4 MB]
  • 06黑马文学-书籍分类列表实现步骤_.mp4 [6.9 MB]
  • 08黑马文学-分类书籍列表条件查询_.mp4 [27.0 MB]
  • 04黑马文学-分类列表测试_.mp4 [4.5 MB]
7_阅读记录、配置及项目部署16 条
  • 09黑马文学-阅读偏好代码测试_.pcwlenv [45.7 MB]
  • 03黑马文学-我的浏览记录实现步骤_.pcwlenv [31.7 MB]
  • 10黑马文学-阅读设置接口设计和实现步骤_.pcwlenv [68.5 MB]
  • 11黑马文学-阅读设置代码实现_.pcwlenv [57.7 MB]
  • 15黑马文学-补充flask-restful_.pcwlenv [37.3 MB]
  • 12黑马文学-阅读设置代码测试_.pcwlenv [28.0 MB]
  • 08黑马文学-阅读偏好代码实现_.pcwlenv [62.8 MB]
  • 06黑马文学-我的浏览记录清除_.pcwlenv [32.5 MB]
  • 04黑马文学-我的浏览记录代码实现_.pcwlenv [129.8 MB]
  • 05黑马文学-我的浏览记录代码测试_.pcwlenv [39.4 MB]
  • 13黑马文学-uWSGI项目部署_.pcwlenv [39.4 MB]
  • 02黑马文学-我的浏览记录接口设计_.pcwlenv [25.6 MB]
  • 14黑马文学-补充异常和日志_.pcwlenv [66.7 MB]
  • 01黑马文学-课程介绍_.pcwlenv [26.2 MB]
  • 07黑马文学-阅读偏好接口设计和实现步骤_.pcwlenv [40.9 MB]
  • 16黑马文学-总结_.pcwlenv [46.3 MB]
6_热门推荐与小说目录17 集
  • 04黑马文学-同类热门推荐代码实现_.mp4 [32.4 MB]
  • 12黑马文学-小说阅读代码实现_.mp4 [26.2 MB]
  • 18黑马文学-总结_.mp4 [13.0 MB]
  • 01黑马文学-课程介绍_.mp4 [3.9 MB]
  • 15黑马文学-小说详情代码实现_.mp4 [31.6 MB]
  • 10黑马文学-小说阅读接口设计_.mp4 [7.3 MB]
  • 14黑马文学-小说详情实现步骤_.mp4 [6.1 MB]
  • 11黑马文学-小说阅读实现步骤_.mp4 [3.9 MB]
  • 07黑马文学-小说目录实现步骤_.mp4 [5.2 MB]
  • 17黑马文学-小说详情代码测试_.mp4 [5.2 MB]
  • 13黑马文学-小说阅读代码测试_.mp4 [12.6 MB]
  • 08黑马文学-小说目录代码实现_.mp4 [25.4 MB]
  • 03黑马文学-同类热门推荐实现步骤_.mp4 [6.0 MB]
  • 09黑马文学-小说目录代码测试_.mp4 [4.9 MB]
  • 16黑马文学-小说详情代码实现补充_.mp4 [5.0 MB]
  • 02黑马文学-同类热门推荐接口设计_.mp4 [5.0 MB]
  • 05黑马文学-同类热门推荐代码测试_.mp4 [4.4 MB]
3_书架管理15 集
  • 15黑马文学-总结_.mp4 [3.8 MB]
  • 09黑马文学-书架添加书籍测试_.mp4 [15.0 MB]
  • 05黑马文学-书架列表代码实现和测试_.mp4 [17.0 MB]
  • 01黑马文学-书籍管理的脚本文件说明_.mp4 [8.6 MB]
  • 11黑马文学-最后阅读实现步骤_.mp4 [7.5 MB]
  • 08黑马文学-书架管理添加书籍代码实现_.mp4 [21.8 MB]
  • 03黑马文学-书架列表实现步骤_.mp4 [4.1 MB]
  • 06黑马文学-书架列表补充说明_.mp4 [10.8 MB]
  • 12黑马文学-最后阅读代码实现1_.mp4 [39.7 MB]
  • 07黑马文学-书架管理添加书籍实现步骤_.mp4 [4.8 MB]
  • 02黑马文学-导入书籍_.mp4 [20.5 MB]
  • 13黑马文学-最后阅读代码实现2_.mp4 [24.1 MB]
  • 14黑马文学-最后阅读测试_.mp4 [6.9 MB]
  • 04黑马文学-书架列表代码实现1_.mp4 [34.0 MB]
  • 10黑马文学-书架删除书籍代码实现和测试_.mp4 [13.2 MB]
2_用户登录14 集
  • 02黑马文学-微信授权流程说明_.mp4 [14.6 MB]
  • 09黑马文学-请求钩子用户权限校验步骤说明_.mp4 [5.7 MB]
  • 08黑马文学-jwt有效期工具实现_.mp4 [20.6 MB]
  • 03黑马文学-微信平台开发流程_.mp4 [27.8 MB]
  • 12黑马文学-添加测试用户_.mp4 [8.9 MB]
  • 06黑马文学-用户登录接口分析和步骤_.mp4 [12.8 MB]
  • 07黑马文学-用户登录代码实现_.mp4 [35.2 MB]
  • 04黑马文学-JWT介绍和pyjwt模块_.mp4 [11.3 MB]
  • 14黑马文学-总结_.mp4 [10.8 MB]
  • 05黑马文学-jwt工具封装_.mp4 [17.1 MB]
  • 11黑马文学-登录验证装饰器实现_.mp4 [11.5 MB]
  • 13黑马文学-测试用户模拟登录_.mp4 [16.5 MB]
  • 01黑马文学-课程介绍_.mp4 [4.1 MB]
  • 10黑马文学-请求钩子用户权健校验代码实现_.mp4 [13.0 MB]
1_项目介绍15 集
  • 13黑马文学-数据库设计书籍卷&章&内容_.mp4 [22.5 MB]
  • 09黑马文学-项目目录工厂函数&蓝图实现_.mp4 [14.4 MB]
  • 02黑马文学-产品原型说明_.mp4 [12.1 MB]
  • 05黑马文学-项目运行方式说明_.mp4 [13.0 MB]
  • 03黑马文学-技术架构说明_.mp4 [5.3 MB]
  • 14黑马文学-数据库迁移_.mp4 [20.8 MB]
  • 08黑马文学-项目目录数据库&脚本管理器&迁移扩展实现_.mp4 [16.7 MB]
  • 04黑马文学-环境配置说明_.mp4 [5.8 MB]
  • 01黑马文学-项目介绍_.mp4 [6.4 MB]
  • 10黑马文学-项目目录代码拆分_.mp4 [20.7 MB]
  • 12黑马文学-数据库设计书籍&搜索&浏览记录_.mp4 [15.8 MB]
  • 15黑马文学-总结_.mp4 [9.2 MB]
  • 11黑马文学-数据库设计书架&书籍分类_.mp4 [27.0 MB]
  • 06黑马文学-项目目录说明_.mp4 [7.1 MB]
  • 07黑马文学-项目目录基本程序实现_.mp4 [12.7 MB]
5_搜索管理12 集
  • 04黑马文学-搜索书本列表代码实现_.mp4 [29.0 MB]
  • 06黑马文学-搜索精准高匹配推荐接口设计_.mp4 [10.4 MB]
  • 02黑马文学-搜索书本列表接口设计_.mp4 [7.1 MB]
  • 09黑马文学-搜索精准高匹配推荐代码实现精准高匹配_.mp4 [35.9 MB]
  • 10黑马文学-搜索精准高匹配推荐代码实现推荐_.mp4 [23.4 MB]
  • 07黑马文学-搜索精准高匹配推荐实现步骤_.mp4 [18.0 MB]
  • 03黑马文学-搜索书本列表实现步骤_.mp4 [4.6 MB]
  • 12黑马文学-总结_.mp4 [13.8 MB]
  • 01黑马文学-课程介绍_.mp4 [8.6 MB]
  • 11黑马文学-搜索精准高匹配推荐代码测试_.mp4 [17.3 MB]
  • 05黑马文学-搜索书本列表代码测试_.mp4 [6.4 MB]
  • 08黑马文学-搜索精准高匹配推荐代码实现关键词处理_.mp4 [13.0 MB]
33Ansible部署9 集
  • 021_快速入门之软件部署(命令执行过程)-.mp4 [30.7 MB]
  • 019_第一天总结-.mp4 [31.7 MB]
  • 018_快速入门之软件部署(简单实践2)-.mp4 [33.2 MB]
  • 013_快速入门之软件部署(主机清单1)-.mp4 [42.5 MB]
  • 016_快速入门之软件部署(配置详解)-.mp4 [45.6 MB]
  • 015_快速入门之软件部署(原理详解)-.mp4 [29.7 MB]
  • 017_快速入门之软件部署(简单实践1)-.mp4 [32.5 MB]
  • 020_快速入门之软件部署(主机进阶实践)-.mp4 [48.3 MB]
  • 014_快速入门之软件部署(主机清单2)-.mp4 [29.5 MB]
43nagios简介和部署10 集
  • 006_快速入门之nagios简介(部署原理)-.mp4 [25.2 MB]
  • 009_快速入门之nagios部署(web环境2)-.mp4 [29.3 MB]
  • 013_快速入门之nagios部署(界面效果)-.mp4 [18.1 MB]
  • 005_快速入门之nagios简介(特点)-.mp4 [17.5 MB]
  • 010_快速入门之nagios部署(nagios安装)-.mp4 [52.2 MB]
  • 008_快速入门之nagios部署(web环境1)-.mp4 [41.3 MB]
  • 011_快速入门之nagios部署(插件安装)-.mp4 [46.3 MB]
  • 004_快速入门之nagios简介(基础知识)-.mp4 [23.4 MB]
  • 012_快速入门之nagios部署(启动服务)-.mp4 [14.0 MB]
  • 007_快速入门之nagios部署(准备环境)-.mp4 [25.1 MB]
21LVS集群基础4 集
  • 003_集群基础之集群简介(小结)-.mp4 [6.2 MB]
  • 000_课程概况-.mp4 [7.2 MB]
  • 001_集群基础之集群简介(集群基础-场景需求+解决方案+访问流程)-.mp4 [25.0 MB]
  • 002_集群基础之集群简介(集群类型-实现方式)-.mp4 [28.1 MB]
31项目管理基础7 集
  • 002_项目管理基础之项目环境(平台环境)-.mp4 [32.8 MB]
  • 006_项目管理基础之项目管理(工具模式)-.mp4 [21.9 MB]
  • 000_课程概况-.mp4 [6.7 MB]
  • 003_项目管理基础之项目环境(项目环境)-.mp4 [14.5 MB]
  • 004_项目管理基础之项目管理(管理方式)-.mp4 [26.7 MB]
  • 005_项目管理基础之项目管理(管理工具)-.mp4 [13.1 MB]
  • 001_项目管理基础之项目环境(项目基础)-.mp4 [42.7 MB]
38ansible进阶之变量6 集
  • 049_ansible进阶之变量进阶(变量-主机属性)-.mp4 [29.7 MB]
  • 048_ansible进阶之变量进阶(变量基础)-.mp4 [24.0 MB]
  • 052_ansible进阶之变量进阶(变量-playbook)-.mp4 [21.1 MB]
  • 053_ansible进阶之变量进阶(变量-专用文件)-.mp4 [31.0 MB]
  • 051_ansible进阶之变量进阶(变量-命令行)-.mp4 [27.7 MB]
  • 050_ansible进阶之变量进阶(变量-主机列表)-.mp4 [41.3 MB]
27keepalived 软件基础4 集
  • 004_快速入门之软件基础(keepalived)-.mp4 [20.4 MB]
  • 007_快速入门之软件基础(VRRP)-.mp4 [25.3 MB]
  • 006_快速入门之软件基础(LVS)-.mp4 [26.2 MB]
  • 005_快速入门之软件基础(软件结构)-.mp4 [34.1 MB]
40ansible进阶之模板12 集
  • 056_ansible进阶之模板(条件1)-.mp4 [44.3 MB]
  • 057_ansible进阶之模板(条件2)-.mp4 [27.5 MB]
  • 058_第三天总结-.mp4 [22.9 MB]
  • 064_ansible进阶之模板(for流程1)-.mp4 [19.1 MB]
  • 060_ansible进阶之模板(迭代进阶1)-.mp4 [21.8 MB]
  • 061_ansible进阶之模板(迭代进阶2)-.mp4 [37.9 MB]
  • 065_ansible进阶之模板(for流程2)-.mp4 [34.0 MB]
  • 055_ansible进阶之模板(快速入门)-.mp4 [45.0 MB]
  • 062_ansible进阶之模板(流程基础1)-.mp4 [17.4 MB]
  • 063_ansible进阶之模板(if流程)-.mp4 [40.7 MB]
  • 054_ansible进阶之模板(模板基础)-.mp4 [24.4 MB]
  • 059_ansible进阶之模板(迭代)-.mp4 [30.2 MB]
42监控知识体系4 集
  • 000_课程概况-.mp4 [6.5 MB]
  • 002_监控知识体系之监控概述(监控原理)-.mp4 [26.3 MB]
  • 003_监控知识体系之监控工具(系统命令+开源软件+第三方平台)-.mp4 [36.0 MB]
  • 001_监控知识体系之监控概述(为什么要监控)-.mp4 [33.0 MB]
11_shell基础之变量7 集
  • 008_shell基础之变量(查看&取消-查看+取消)-.mp4 [11.3 MB]
  • 010_shell基础之小结-.mp4 [19.8 MB]
  • 005_shell基础之变量(变量基础-定位+分类)-.mp4 [14.0 MB]
  • 006_shell基础之变量(本地变量-定义+普通变量+命令变量)-.mp4 [29.5 MB]
  • 007_shell基础之变量(全局变量-定义+查看+定义)-.mp4 [14.2 MB]
  • 010_shell基础之变量(内置变量-精确截取+默认值)-.mp4 [26.5 MB]
  • 009_shell基础之变量(内置变量-定义+脚本文件)-.mp4 [33.8 MB]
28keepalived 软件部署9 集
  • 011_快速入门之软件部署(配置实践2)-.mp4 [10.9 MB]
  • 008_快速入门之软件部署(安装软件)-.mp4 [46.5 MB]
  • 016_快速入门之小结-.mp4 [35.2 MB]
  • 013_快速入门之软件部署(负载均衡1)-.mp4 [50.0 MB]
  • 012_快速入门之软件部署(故障演练)-.mp4 [30.0 MB]
  • 014_快速入门之软件部署(负载均衡2)-.mp4 [43.8 MB]
  • 009_快速入门之软件部署(配置简介)-.mp4 [38.0 MB]
  • 010_快速入门之软件部署(配置实践)-.mp4 [40.7 MB]
  • 015_快速入门之软件部署(负载均衡3)-.mp4 [17.7 MB]
12_shell核心知识表达式6 集
  • 012_核心知识之表达式(条件表达式-逻辑+文件)-.mp4 [24.8 MB]
  • 015_核心知识之表达式(数组-简介+定义+查看)-.mp4 [27.0 MB]
  • 013_核心知识之表达式(条件表达式-数字+字符串)-.mp4 [14.8 MB]
  • 014_核心知识之表达式(计算表达式-场景+格式+实践)-.mp4 [14.9 MB]
  • 011_核心知识之表达式(测试语句-应用场景+语句格式)-.mp4 [14.7 MB]
  • 016_核心知识之表达式(数组-增删改查)-.mp4 [26.8 MB]
23LVS快速入门之NAT实战13 集
  • 015_lvs快速入门之NAT实践(简单实践-web服务+lvs集群设置)-.mp4 [31.5 MB]
  • 022_lvs快速入门之NAT实践(进阶实践2-集群实践+小结)-.mp4 [12.1 MB]
  • 019_lvs快速入门之NAT实践(进阶实践1-实践小结+数据包分析)-.mp4 [25.2 MB]
  • 013_lvs快速入门之NAT实践(简单实践-案例需求+需求分析+关键点分析)-.mp4 [24.3 MB]
  • 021_lvs快速入门之NAT实践(进阶实践2-https实践)-.mp4 [27.3 MB]
  • 020_lvs快速入门之NAT实践(进阶实践2-场景需求+需求分析+关键点分析+实践)-.mp4 [23.0 MB]
  • 023_lvs快速入门之NAT实践(小结)-.mp4 [20.2 MB]
  • 011_lvs快速入门之NAT实践(前置知识-网络设备+基本环境)-.mp4 [25.6 MB]
  • 016_lvs快速入门之NAT实践(原理详解-流程详解+数据包详解+请求流程)-.mp4 [27.9 MB]
  • 014_lvs快速入门之NAT实践(简单实践-案例需求+基础环境设置)-.mp4 [21.5 MB]
  • 012_lvs快速入门之NAT实践(NAT简介-模型简介+模型分析)-.mp4 [23.3 MB]
  • 017_lvs快速入门之NAT实践(应用技巧-原理技巧+应用技巧)-.mp4 [30.0 MB]
  • 018_lvs快速入门之NAT实践(进阶实践-场景需求+需求分析+关键点分析+实践)-.mp4 [34.3 MB]
03_Linux基本命令28 集
  • 012-基本命令5-磁盘内存命令-.mp4 [10.8 MB]
  • 002-远程连接工具-.mp4 [18.2 MB]
  • 010-基本命令3-.mp4 [20.1 MB]
  • 013-基本命令6-文件内容-.mp4 [42.7 MB]
  • 011-基本命令4-帮助命令-.mp4 [19.8 MB]
  • 014-基本命令-日期时间-.mp4 [2.0 GB]
  • 001-基本命令-其他命令-.mp4 [735.1 MB]
  • 015-基本命令-管道命令-.mp4 [982.9 MB]
20iptables快速入门之地址转换5 集
  • 035_iptables快速入门之规则进阶(地址转换-SNAT进阶实践)-.mp4 [18.1 MB]
  • 036_iptables快速入门之规则进阶(地址转换-DNAT实践)-.mp4 [24.3 MB]
  • 034_iptables快速入门之规则进阶(地址转换-SNAT实践)-.mp4 [29.6 MB]
  • 037_iptables快速入门之规则进阶(小结)-.mp4 [30.8 MB]
  • 033_iptables快速入门之规则进阶(地址转换-案例需求+准备环境)-.mp4 [39.4 MB]
01_Linux系统安装和认识6 集
  • 006-系统认识-.mp4 [12.9 MB]
  • 001-linux概述-.mp4 [18.0 MB]
  • 002-虚拟机创建-.mp4 [41.5 MB]
  • 003-linux安装一-.mp4 [34.0 MB]
  • 004-linux安装二-.mp4 [7.9 MB]
  • 005-备份操作系统-.mp4 [23.7 MB]
26keepalived 集群基础4 集
  • 001_集群基础之集群简介(集群分类)-.mp4 [18.7 MB]
  • 000_课程概况-.mp4 [4.2 MB]
  • 002_集群基础之集群简介(可用性指标)-.mp4 [47.7 MB]
  • 003_集群基础之集群简介(高可用方式)-.mp4 [42.6 MB]
14_shell核心知识之常见命令9 集
  • 031_核心知识之常见命令(awk2)-.mp4 [29.6 MB]
  • 033_核心知识之常见命令(awk4)-.mp4 [31.2 MB]
  • 030_核心知识之常见命令(awk1)-.mp4 [25.0 MB]
  • 034_核心知识之常见命令(find1)-.mp4 [44.9 MB]
  • 032_核心知识之常见命令(awk3)-.mp4 [19.9 MB]
  • 029_核心知识之常见命令(sed2)-.mp4 [24.9 MB]
  • 035_核心知识之常见命令(find2)-.mp4 [26.6 MB]
  • 027_核心知识之常见命令(grep)-.mp4 [31.6 MB]
  • 036_核心知识之小结-.mp4 [23.1 MB]
32Ansible安装和简单实用6 集
  • 008_快速入门之软件部署(部署简介+准备工作1)-.mp4 [31.4 MB]
  • 011_快速入门之软件部署(简单使用1)-.mp4 [41.8 MB]
  • 012_快速入门之软件部署(简单使用2)-.mp4 [32.6 MB]
  • 010_快速入门之软件部署(软件安装)-.mp4 [15.6 MB]
  • 009_快速入门之软件部署(部署简介+准备工作2)-.mp4 [17.8 MB]
  • 007_快速入门之基础知识(简介+功能简介)-.mp4 [29.8 MB]
46远程监控11 条
  • 038_第一天总结-.pcwlenv [31.1 MB]
  • 037_快速入门之远程监控(脚本开发2)-.pcwlenv [37.6 MB]
  • 039_第二天总结-.pcwlenv [25.6 MB]
  • 030_快速入门之远程监控(准备工作)-.pcwlenv [38.3 MB]
  • 036_快速入门之远程监控(脚本开发1)-.pcwlenv [38.6 MB]
  • 033_快速入门之远程监控(命令详解)-.pcwlenv [45.4 MB]
  • 035_快速入门之远程监控(nrpe实践2)-.pcwlenv [23.2 MB]
  • 031_快速入门之远程监控(远程主机部署1)-.pcwlenv [38.5 MB]
  • 029_快速入门之远程监控(被动流程)-.pcwlenv [17.5 MB]
  • 034_快速入门之远程监控(nrpe实践1)-.pcwlenv [37.3 MB]
  • 032_快速入门之远程监控(远程主机部署2)-.pcwlenv [45.3 MB]
06_软件管理和计划任务5 集
  • 019-软件管理-源码包-.mp4 [41.1 MB]
  • 001-运行模式-.mp4 [27.9 MB]
  • 002-计划任务-at-.mp4 [27.3 MB]
  • 003-计划任务-cron-.mp4 [47.9 MB]
  • 020-软件管理-rpm和yum-.mp4 [532.0 KB]
02_Linux基本命令13 集
  • 009-基本命令2-压缩解压缩-.mp4 [66.0 MB]
  • 007-命令入门-.mp4 [36.0 MB]
  • 008-基本命令1-.mp4 [41.3 MB]
07_ssh、日志管理和网络管理7 集
  • 006-ssh-修改sshd端口号-.mp4 [10.2 MB]
  • 007-ssh-远程传输命令-.mp4 [34.1 MB]
  • 004-ssh-基于口令验证-.mp4 [19.7 MB]
  • 009-网络管理-.mp4 [56.8 MB]
  • 010-系统基本优化-.mp4 [26.7 MB]
  • 005-ssh-基于秘钥安全验证-.mp4 [20.3 MB]
  • 008-日志管理-.mp4 [50.9 MB]
10_运维和shell脚本5 集
  • 000_课程概况-.mp4 [6.2 MB]
  • 003_shell基础之shell脚本(创建脚本-方式+命名+内容+注释)-.mp4 [18.2 MB]
  • 001_shell基础之运维&shell(运维基础-运维定位+工作范围+运维&shell)-.mp4 [16.6 MB]
  • 004_shell基础之shell脚本(脚本使用-执行方式+开发规范)-.mp4 [32.9 MB]
  • 002_shell基础之运维&shell(shell简介-shell定位+shell分类+使用方式)-.mp4 [22.1 MB]
15安全知识体系7 集
  • 006_安全知识体系之防火墙基础(功能-分层管控+数据包过滤)-.mp4 [35.1 MB]
  • 007_安全知识体系之小结-.mp4 [13.1 MB]
  • 001_安全知识体系之安全概述(安全现状-安全场景+安全案例+项目现状)-.mp4 [17.8 MB]
  • 003_安全知识体系之安全概述(安全措施-角色定位+安全措施)-.mp4 [12.8 MB]
  • 002_安全知识体系之安全概述(安全体系-硬件+基础+应用+业务+运营)-.mp4 [21.1 MB]
  • 000_课程概况-.mp4 [7.2 MB]
  • 004_安全知识体系之防火墙基础(简介-场景需求+简介)-.mp4 [22.8 MB]
22LVS快速入门7 集
  • 006_lvs快速入门之lvs快速入门(安装软件-命令简介)-.mp4 [30.1 MB]
  • 004_lvs快速入门之lvs基础(防火墙回顾-五表五链+应用场景+地址转换)-.mp4 [23.6 MB]
  • 007_lvs快速入门之lvs快速入门(集群命令-查看+增加+编辑+删除)-.mp4 [26.8 MB]
  • 005_lvs快速入门之lvs基础(简介-结构)-.mp4 [55.2 MB]
  • 008_lvs快速入门之lvs快速入门(主机命令-查看+增加+编辑+删除)-.mp4 [37.2 MB]
  • 009_lvs快速入门之lvs快速入门(规则命令-保存+清空+载入+服务)-.mp4 [45.5 MB]
  • 010_lvs快速入门之lvs快速入门(小结)-.mp4 [13.5 MB]
44nagios配置详解18 集
  • 020_快速入门之配置详解(mysql实践2)-.mp4 [20.1 MB]
  • 019_快速入门之配置详解(mysql实践1)-.mp4 [48.2 MB]
  • 021_快速入门之配置详解(原理详解)-.mp4 [29.8 MB]
  • 018_快速入门之配置详解(简单实践2)-.mp4 [25.5 MB]
  • 015_快速入门之配置详解(目录结构+配置详解)-.mp4 [46.4 MB]
  • 014_快速入门之配置详解(目录结构)-.mp4 [37.3 MB]
  • 016_快速入门之配置详解(核心资源)-.mp4 [39.4 MB]
  • 017_快速入门之配置详解(简单实践1)-.mp4 [47.1 MB]
17iptables快速入门之五表五链6 集
  • 019_iptables快速入门之五表五链(小结)-.mp4 [27.9 MB]
  • 017_iptables快速入门之五表五链(表实践-信息查看+规则实践)-.mp4 [27.4 MB]
  • 015_iptables快速入门之五表五链(链实践-顺序+增删改)-.mp4 [34.4 MB]
  • 018_iptables快速入门之五表五链(表链关系-关系+优先级+编写+场景)-.mp4 [56.4 MB]
  • 014_iptables快速入门之五表五链(链基础-简介+详解+关系)-.mp4 [28.1 MB]
  • 016_iptables快速入门之五表五链(表简介-简介+详解)-.mp4 [37.5 MB]
41ansible进阶之Role13 集
  • 070_ansible进阶之Role(role结构)-.mp4 [16.3 MB]
  • 078_ansible进阶之Role(综合实践4)-.mp4 [36.9 MB]
  • 072_ansible进阶之Role(扩展功能1)-.mp4 [22.1 MB]
  • 073_ansible进阶之Role(扩展功能2)-.mp4 [46.4 MB]
  • 069_ansible进阶之Role(简单案例3)-.mp4 [5.6 MB]
  • 066_ansible进阶之Role(角色基础)-.mp4 [28.1 MB]
  • 075_ansible进阶之Role(综合实践)-.mp4 [20.6 MB]
  • 067_ansible进阶之Role(简单案例1)-.mp4 [29.0 MB]
  • 068_ansible进阶之Role(简单案例2)-.mp4 [47.9 MB]
  • 071_ansible进阶之Role(角色管理)-.mp4 [36.3 MB]
  • 076_ansible进阶之Role(综合实践2)-.mp4 [40.8 MB]
  • 074_ansible进阶之Role(扩展功能3)-.mp4 [14.8 MB]
  • 079_第四天总结-.mp4 [24.8 MB]
37playbook任务依赖和标签5 集
  • 043_快速入门之playbook(异常中断)-.mp4 [46.6 MB]
  • 046_快速入门之playbook(标签1)-.mp4 [28.7 MB]
  • 047_快速入门之playbook(标签2)-.mp4 [41.4 MB]
  • 044_快速入门之playbook(任务依赖1)-.mp4 [29.2 MB]
  • 045_快速入门之playbook(任务依赖2)-.mp4 [29.9 MB]
16iptables快速入门之日常操作6 集
  • 008_快速入门之iptables简介(基础-结构+关联)-.mp4 [24.5 MB]
  • 012_iptables快速入门之日常操作(规则简介-定义+简介+格式+动作)-.mp4 [42.6 MB]
  • 009_iptables快速入门之日常操作(firewall快速入门)-.mp4 [37.7 MB]
  • 013_iptables快速入门之日常操作(规则实践-增+删+改)-.mp4 [51.5 MB]
  • 011_iptables快速入门之日常操作(简单实践-增删改查)-.mp4 [70.1 MB]
  • 010_iptables快速入门之日常操作(iptables快速入门)-.mp4 [21.0 MB]
08_apache安装和配置9 集
  • 002-apache配置服务路劲认识-.mp4 [7.9 MB]
  • 004-配置详解1-.mp4 [30.8 MB]
  • 010-配置详解总结-.mp4 [14.6 MB]
  • 009-配置详解6-.mp4 [38.5 MB]
  • 005-配置详解2-.mp4 [28.4 MB]
  • 003-apache基本概念-.mp4 [20.9 MB]
  • 001-apache概述安装-.mp4 [37.6 MB]
  • 007-配置详解4-.mp4 [34.5 MB]
  • 008-配置详解5-.mp4 [56.7 MB]
30keepalived 配置详解27 集
  • 023_快速入门之配置详解(状态健康检测1)-.mp4 [37.6 MB]
  • 025_快速入门之配置详解(TCP状态健康检测)-.mp4 [35.0 MB]
  • 027_快速入门之配置详解(日志配置)-.mp4 [45.0 MB]
  • 022_快速入门之配置详解(虚拟主机配置)-.mp4 [43.6 MB]
  • 024_快速入门之配置详解(状态健康检测2)-.mp4 [18.3 MB]
  • 028_快速入门之配置详解(小结)-.mp4 [23.7 MB]
  • 026_快速入门之配置详解(友情提示)-.mp4 [42.8 MB]
25LVS TUN实践9 集
  • 044_lvs快速入门之小结-.mp4 [20.9 MB]
  • 041_lvs快速入门之TUN实践(简单实践2)-.mp4 [28.7 MB]
  • 042_lvs快速入门之TUN实践(简单实践3)-.mp4 [27.0 MB]
  • 037_lvs快速入门之TUN实践(前置知识2)-.mp4 [9.9 MB]
  • 043_lvs快速入门之TUN实践(原理详解)-.mp4 [22.8 MB]
  • 038_lvs快速入门之TUN实践(隧道实践)-.mp4 [51.3 MB]
  • 039_lvs快速入门之TUN实践(TUN简介)-.mp4 [16.8 MB]
  • 040_lvs快速入门之TUN实践(简单实践1)-.mp4 [19.5 MB]
  • 036_lvs快速入门之TUN实践(前置知识)-.mp4 [30.3 MB]
24LVS调度策略和DR实践11 集
  • 026_lvs快速入门之调度策略(wrr实践)-.mp4 [18.3 MB]
  • 028_lvs快速入门之DR实践(前置知识-ARP表+交换机原理+地址冲突)-.mp4 [38.4 MB]
  • 032_lvs快速入门之DR实践(简单实践-案例实践2)-.mp4 [25.8 MB]
  • 025_lvs快速入门之调度策略(调度基础+静态方法+动态方法)-.mp4 [35.0 MB]
  • 031_lvs快速入门之DR实践(简单实践-案例实践1)-.mp4 [34.1 MB]
  • 027_lvs快速入门之调度策略(sh实践)-.mp4 [12.8 MB]
  • 035_lvs快速入门之DR实践(应用技巧)-.mp4 [24.3 MB]
  • 029_lvs快速入门之DR实践(DR模型-模型简介+模型分析)-.mp4 [20.0 MB]
  • 034_lvs快速入门之DR实践(原理详解)-.mp4 [16.0 MB]
  • 030_lvs快速入门之DR实践(简单实践-案例需求+需求分析+技术点分析)-.mp4 [20.2 MB]
  • 033_lvs快速入门之DR实践(简单实践-案例实践3)-.mp4 [13.8 MB]
35文件模块、应用模块和命令8 集
  • 029_快速入门之常用模块(文件模块2)-.mp4 [24.5 MB]
  • 032_快速入门之常用模块(应用模块2)-.mp4 [34.5 MB]
  • 031_快速入门之常用模块(应用模块1)-.mp4 [43.5 MB]
  • 028_快速入门之常用模块(文件模块1)-.mp4 [35.4 MB]
  • 034_快速入门之常用模块(系列命令2)-.mp4 [35.4 MB]
  • 030_快速入门之常用模块(文件模块3)-.mp4 [29.6 MB]
  • 035_快速入门之常用模块(系列命令3)-.mp4 [16.5 MB]
  • 033_快速入门之常用模块(系列命令1)-.mp4 [44.7 MB]
09_apache虚拟主机、防盗链和日志切割7 集
  • 011-基于ip的虚拟主机-.mp4 [23.4 MB]
  • 015-防盗链-.mp4 [27.9 MB]
  • 016-域名跳转-.mp4 [24.6 MB]
  • 013-基于端口的虚拟主机-.mp4 [21.0 MB]
  • 012-基于域名的虚拟主机-.mp4 [17.1 MB]
  • 018-日志切割-cronolog-.mp4 [18.2 MB]
  • 017-日志切割-rotatelogs-.mp4 [14.3 MB]
19iptables快速入门之web扩展和网络防火墙6 条
  • 030_iptables快速入门之规则进阶(web扩展-连接状态实践)-.pcwlenv [31.5 MB]
  • 031_iptables快速入门之规则进阶(网络防火墙-需求场景+基本环境)-.pcwlenv [31.7 MB]
  • 028_iptables快速入门之规则进阶(web扩展-内容扩展实践)-.pcwlenv [24.4 MB]
  • 029_iptables快速入门之规则进阶(web扩展-ip并发+内容并发实践)-.pcwlenv [56.2 MB]
  • 032_iptables快速入门之规则进阶(网络防火墙-web服务+防火墙实践)-.pcwlenv [37.2 MB]
  • 027_iptables快速入门之规则进阶(web扩展-时间扩展实践)-.pcwlenv [33.0 MB]
13_shell核心知识常见符号和流程控制10 集
  • 020_核心知识之简单流程控制(if语句-多分支+实践)-.mp4 [27.5 MB]
  • 022_核心知识之简单流程控制(循环语句-for+while+until)-.mp4 [29.9 MB]
  • 025_核心知识之复杂流程控制(函数-简介+简单+传参)-.mp4 [26.7 MB]
  • 018_核心知识之常见符号(其他符号)-.mp4 [28.3 MB]
  • 023_核心知识之简单流程控制(循环退出-简介+break+break n)-.mp4 [30.4 MB]
  • 024_核心知识之简单流程控制(循环退出-continue+exit)-.mp4 [20.1 MB]
  • 019_核心知识之简单流程控制(if语句-单分支+双分支)-.mp4 [19.5 MB]
  • 021_核心知识之简单流程控制(case语句-格式+实践)-.mp4 [27.6 MB]
  • 026_核心知识之复杂流程控制(函数-脚本传参+生产用法)-.mp4 [22.3 MB]
  • 017_核心知识之常见符号(重定向+管道符)-.mp4 [14.5 MB]
18iptables快速入门之匹配7 集
  • 026_iptables快速入门之规则进阶(扩展匹配-地址扩展实践)-.mp4 [28.6 MB]
  • 020_iptables快速入门之规则进阶(普通匹配1-匹配条件详解)-.mp4 [24.7 MB]
  • 024_iptables快速入门之规则进阶(扩展匹配-扩展简介+扩展分类)-.mp4 [24.1 MB]
  • 021_iptables快速入门之规则进阶(普通匹配1-多目标实践)-.mp4 [43.5 MB]
  • 022_iptables快速入门之规则进阶(普通匹配1-目标地址实践)-.mp4 [27.3 MB]
  • 023_iptables快速入门之规则进阶(普通匹配2-协议实践+接口实践)-.mp4 [53.5 MB]
  • 025_iptables快速入门之规则进阶(扩展匹配-端口扩展实践)-.mp4 [48.3 MB]
34日常模块和系统模块6 集
  • 024_快速入门之常用模块(系统模块1)-.mp4 [46.7 MB]
  • 025_快速入门之常用模块(系统模块2)-.mp4 [29.9 MB]
  • 023_快速入门之常用模块(日常模块2)-.mp4 [33.7 MB]
  • 026_快速入门之常用模块(系统模块3)-.mp4 [33.2 MB]
  • 027_快速入门之常用模块(系统模块4)-.mp4 [23.1 MB]
  • 022_快速入门之常用模块(日常模块1)-.mp4 [41.9 MB]
36playbook基础7 集
  • 036_快速入门之playbook(基础)-.mp4 [23.6 MB]
  • 040_快速入门之playbook(基础属性2)-.mp4 [23.5 MB]
  • 041_快速入门之playbook(基础属性3)-.mp4 [35.5 MB]
  • 039_快速入门之playbook(基础属性1)-.mp4 [55.3 MB]
  • 037_快速入门之playbook(YAML详解)-.mp4 [50.8 MB]
  • 042_快速入门之playbook(基础属性4)-.mp4 [23.1 MB]
  • 038_第二天总结-.mp4 [28.6 MB]
29keepalived 配置详解15 集
  • 017_快速入门之配置详解(全局配置段)-.mp4 [40.4 MB]
  • 018_快速入门之配置详解(VRRP配置段)-.mp4 [49.5 MB]
  • 019_快速入门之配置详解(状态检测1)-.mp4 [34.3 MB]
  • 021_快速入门之配置详解(状态检测3)-.mp4 [22.1 MB]
  • 020_快速入门之配置详解(状态检测2)-.mp4 [42.0 MB]
04_vim编辑器5 集
  • 008-vim编辑器-案例-.mp4 [6.5 MB]
  • 006-vim编辑器-编辑模式和小结-.mp4 [10.5 MB]
  • 003-vim编辑器介绍及打开文件-.mp4 [21.1 MB]
  • 004-vim编辑器-命令行模式操作-.mp4 [23.3 MB]
  • 007-vim编辑器-实用功能-.mp4 [29.1 MB]
45nagios配置详解27 集
  • 023_快速入门之配置详解(http实践2)-.mp4 [23.4 MB]
  • 022_快速入门之配置详解(http实践1)-.mp4 [44.2 MB]
  • 028_快速入门之配置详解(配置角色)-.mp4 [23.2 MB]
  • 025_快速入门之配置详解(告警配置)-.mp4 [38.7 MB]
  • 027_快速入门之配置详解(邮件告警2)-.mp4 [40.0 MB]
  • 024_快速入门之配置详解(http实践3)-.mp4 [29.0 MB]
  • 026_快速入门之配置详解(邮件告警1)-.mp4 [37.9 MB]
05_用户、组和权限管理10 集
  • 015-权限管理-字母形式设置权限-.mp4 [16.9 MB]
  • 013-用户与组-组管理-.mp4 [12.0 MB]
  • 016-权限管理-数字形式设置权限-.mp4 [26.5 MB]
  • 011-用户与组-设置密码修改用户信息-.mp4 [23.0 MB]
  • 018-权限管理-umask默认权限-.mp4 [16.1 MB]
  • 012-用户与组-删除用户-.mp4 [18.0 MB]
  • 017-权限管理-所有者和所属组管理-.mp4 [10.4 MB]
  • 014-权限管理-权限概述查看权限-.mp4 [19.7 MB]
  • 010-用户与组-创建用户-.mp4 [17.6 MB]
  • 009-用户与组-介绍-.mp4 [5.4 MB]
39keepalived 原理详解和综合实践6 集
  • 032_快速入门之综合实践(双主方式2)-.mp4 [38.2 MB]
  • 033_快速入门之综合实践(双主方式3)-.mp4 [31.6 MB]
  • 030_快速入门之原理详解(路由详解)-.mp4 [44.0 MB]
  • 029_快速入门之原理详解(结构详解)-.mp4 [46.0 MB]
  • 034_快速入门之综合实践(小结)-.mp4 [14.4 MB]
  • 031_快速入门之综合实践(双主方式1)-.mp4 [16.7 MB]
01_爬虫基础9 集
  • 07.http与https的区别_.mp4 [27.6 MB]
  • 01.爬虫特点介绍_.mp4 [35.4 MB]
  • 02.课程结构_.mp4 [12.7 MB]
  • 09.创建的响应状态码_.mp4 [75.6 MB]
  • 03.鐖櫕鐨勬蹇礯.mp4 [32.7 MB]
  • 06.鐖櫕鐨勬祦绋媉.mp4 [46.2 MB]
  • 05.鐖櫕鐨勫垎绫籣.mp4 [68.2 MB]
  • 10.浏览器运行过程_.mp4 [148.4 MB]
  • 08.常见的请求头与响应头_.mp4 [164.3 MB]
06_MongoDB数据库14 集
  • 08.mongdb插入数据_.mp4 [16.3 MB]
  • 17.pymongo使用_.mp4 [34.8 MB]
  • 10.mongodb查询结果操作_.mp4 [19.8 MB]
  • 07.mongodb的数据类型_.mp4 [12.7 MB]
  • 16.mongodb权限管理-普通用户_.mp4 [13.7 MB]
  • 09.mongodb查询数据_.mp4 [26.3 MB]
  • 12.聚合管道-分组管道_.mp4 [29.7 MB]
  • 06.mongdb简单使用-集合操作_.mp4 [19.7 MB]
  • 03.mongodb简单使用-测试启动_.mp4 [47.1 MB]
  • 05.mongodb简单使用-数据库操作_.mp4 [7.9 MB]
  • 15.mongodb的权限管理-管理用户_.mp4 [10.3 MB]
  • 13.聚合管道-其他管道_.mp4 [30.1 MB]
  • 02.mongodb的安装_.mp4 [38.2 MB]
  • 04.mongodb简单使用-生产启动_.mp4 [91.6 MB]
07_scrapy基础20 集
  • 07.项目开发流程-4完成爬虫_.mp4 [61.9 MB]
  • 22.中间件-随机ip代理_.mp4 [204.4 MB]
  • 14.scrapy模拟登陆-cookies参数使用_.mp4 [31.4 MB]
  • 16.scrapy管道的使用_.mp4 [64.8 MB]
  • 23.中间件-selenium动态加载_.mp4 [282.7 MB]
  • 08.项目开发流程-5保存数据_.mp4 [122.6 MB]
  • 12.请求对象-其他参数_.mp4 [14.8 MB]
  • 13.请求对象-meta传参_.mp4 [29.6 MB]
  • 05.项目开发流程-2创建项目_.mp4 [8.9 MB]
  • 03.scrapy-各模块功能_.mp4 [10.9 MB]
  • 01.scrapy-姒傚康&浣滅敤_.mp4 [6.4 MB]
  • 11.请求对象-案例-网易招聘_.mp4 [55.8 MB]
  • 15.scrapy模拟登陆-FormRequest发送post请求_.mp4 [34.3 MB]
  • 09.项目开发流程-数据建模&流程完善_.mp4 [22.0 MB]
  • 19.中间件-分类与作用_.mp4 [95.6 MB]
  • 20.中间件-豆瓣爬虫_.mp4 [169.9 MB]
  • 21.中间件-随机请求头_.mp4 [115.0 MB]
  • 10.请求对象-请求&网易招聘简介_.mp4 [7.3 MB]
  • 04.项目开发流程-1框架安装&流程简介_.mp4 [3.9 MB]
  • 06.项目开发流程-3创建爬虫_.mp4 [25.1 MB]
03_数据提取11 集
  • 11.xpath语法-其他常用语法_.mp4 [16.5 MB]
  • 03.常用数据解析方法_.mp4 [18.3 MB]
  • 06.jsonpath-妗堜緥-鎷夐挬_.mp4 [36.0 MB]
  • 08.xpathhelper简介_安装_.mp4 [64.4 MB]
  • 07.lxml绠€浠媉.mp4 [29.7 MB]
  • 09.xpath语法-基础节点选择_.mp4 [149.4 MB]
  • 04.jsonpath-场景-安装-使用_.mp4 [54.8 MB]
  • 13.鐧惧害璐村惂_.mp4 [90.7 MB]
  • 12.lxml使用_.mp4 [137.2 MB]
  • 01.数据提取-响应内容的分类_.mp4 [168.4 MB]
  • 10.xpath语法-节点修饰语法_.mp4 [458.1 MB]
02_requests模块15 集
  • 12.requests模块-post请求_金山翻译案例_.mp4 [170.9 MB]
  • 8.requests模块-cookiejar对象的处理_.mp4 [26.2 MB]
  • 5.requests模块-发送带参数的请求_.mp4 [107.8 MB]
  • 11.requests模块-verify参数与ca证书_.mp4 [44.1 MB]
  • 10.requests模块-代理proxies使用_.mp4 [128.1 MB]
  • 13.requests-post数据来源_.mp4 [199.7 MB]
  • 9.requests模块-timeout参数_.mp4 [32.5 MB]
  • 4.requests模块-发送带请求头的请求_.mp4 [92.9 MB]
  • 15.案例-github模拟登陆_.mp4 [270.1 MB]
  • 14.requests模块-session_.mp4 [19.8 MB]
  • 3.requests模块-响应对象常用的参数和方法_.mp4 [39.5 MB]
  • 6.requests模块-在headers中设置cookies参数_.mp4 [92.5 MB]
  • 7.requests模块-cookies参数的使用_.mp4 [89.6 MB]
  • 1.requests模块-简介-安装-使用_.mp4 [52.2 MB]
  • 2.requests模块-响应对象的text与content之间的区别_.mp4 [49.6 MB]
10_appium3 集
  • 03.appium环境联调测试_.mp4 [120.9 MB]
  • 04.appium使用_.mp4 [156.9 MB]
  • 01.appium绠€浠媉.mp4 [48.3 MB]
05_反爬与反反爬18 条
  • 10.chrome浏览器的使用_.pcwlenv [28.6 MB]
  • 13.js解析-js代码分析_.pcwlenv [31.3 MB]
  • 04.反爬与反反爬-基于身份识别的反爬_.pcwlenv [14.4 MB]
  • 02.反爬与反反爬-什么样的爬虫会被反_.pcwlenv [7.5 MB]
  • 03.反爬与反反爬-常见概念与反爬方向_.pcwlenv [10.5 MB]
  • 06.反爬与反反爬-基于数据加密进行反爬_.pcwlenv [40.0 MB]
  • 07.验证码-验证码的知识_.pcwlenv [9.7 MB]
  • 16.有道翻译分析_.pcwlenv [31.8 MB]
  • 18.有道翻译实现_.pcwlenv [40.4 MB]
  • 14.js解析-js2py使用_.pcwlenv [30.3 MB]
  • 15.js解析-人人网登陆_.pcwlenv [55.9 MB]
  • 08.验证码-图像识别引擎_.pcwlenv [20.7 MB]
  • 05.反爬与反反爬-及与爬虫行为的反爬_.pcwlenv [40.2 MB]
  • 09.验证码-打码平台_.pcwlenv [41.5 MB]
  • 12.js解析-定位js文件_.pcwlenv [24.7 MB]
  • 01.反爬与反反爬-反爬原因_.pcwlenv [7.5 MB]
  • 11.js解析-人人网登录分析_.pcwlenv [24.5 MB]
  • 17.hashlib使用_.pcwlenv [37.3 MB]
08_scrapy-redis9 集
  • 10.scrapy-redis-京东爬虫-修改成分布式爬虫_.mp4 [236.1 MB]
  • 04.scrapy-redis-分布式爬虫实现_.mp4 [285.8 MB]
  • 01.scrapy-redis-分布式的概念_原理_.mp4 [169.7 MB]
  • 03.scrapy-redis-婧愮爜鍒嗘瀽_.mp4 [342.3 MB]
  • 05.scrapy-redis-分布式爬虫编写流程_.mp4 [38.3 MB]
  • 08.scrapy-redis-京东爬虫-图书列表页面_.mp4 [197.0 MB]
  • 06.scrapy-redis-京东爬虫-简介_.mp4 [187.4 MB]
  • 07.scrapy-redis-京东爬虫-图书分类页面_.mp4 [199.0 MB]
  • 09.scrapy-redis-京东爬虫-图书价格_.mp4 [216.3 MB]
09_scrapy其他7 集
  • 04.scrpay配置-常用配置_.mp4 [127.2 MB]
  • 07.使用Gerapy进行爬虫管理_.mp4 [104.0 MB]
  • 01.splash-介绍_环境配置_.mp4 [111.8 MB]
  • 05.scrapy配置-其他配置_.mp4 [69.8 MB]
  • 06.使用scrapyd进行爬虫部署_.mp4 [130.0 MB]
  • 02.splash-使用_.mp4 [118.5 MB]
  • 03.scrapy-日志信息_.mp4 [142.7 MB]
04_selenium11 集
  • 06.selenium-鍏冪礌瀹氫綅_.mp4 [184.1 MB]
  • 01.selenium-介绍_效果展示_.mp4 [87.9 MB]
  • 07.selenium-鍏冪礌鎿嶄綔_.mp4 [54.5 MB]
  • 13.selenium-配置对象_.mp4 [27.1 MB]
  • 14.selenium-案例-斗鱼直播_.mp4 [568.1 MB]
  • 04.selenium-简单使用_.mp4 [36.2 MB]
  • 09.selenium-绐楀彛鍒囨崲_.mp4 [125.8 MB]
  • 12.selenium-椤甸潰绛夊緟_.mp4 [77.7 MB]
  • 05.selenium-driver灞炴€у拰鏂规硶_.mp4 [27.5 MB]
  • 02.selenium的工作原理_.mp4 [21.9 MB]
  • 03.selenium-模块与driver的安装_.mp4 [98.8 MB]
第二章 算法效果衡量标准10 集
  • 02_06_聚类算法_效果衡量_图片压缩实战-.mp4 [70.0 MB]
  • 02_09_聚类算法_效果衡量标准_聚类效果评估_作业-.mp4 [29.0 MB]
  • 02_03_聚类算法_效果衡量_SC系数-.mp4 [170.0 MB]
  • 02_00_聚类算法_效果衡量_导入-.mp4 [19.3 MB]
  • 02_08_聚类算法_效果衡量_总结-.mp4 [37.4 MB]
  • 02_07_聚类算法_效果衡量_案例2_图片压缩实战_实践-.mp4 [117.2 MB]
  • 02_04_聚类算法_效果衡量标准_CH系数-.mp4 [218.0 MB]
  • 02_05_聚类算法_衡量标准_优缺点-.mp4 [53.5 MB]
  • 02_01_聚类算法_效果衡量_SSE-.mp4 [198.4 MB]
  • 02_02_聚类算法_衡量标准_肘部法-.mp4 [99.3 MB]
09_聚类算法_综合实践_客户价值分析_作业1 集
  • 05_06_聚类算法_综合实践_客户价值分析_作业-.mp4 [60.7 MB]
06_聚类算法_复习1 集
  • 05_03_聚类算法_复习-.mp4 [15.9 MB]
07_聚类算法_总结与回顾1 集
  • 05_04_聚类算法_总结与回顾-.mp4 [99.0 MB]
08_聚类算法_学习提升+资料推荐1 集
  • 05_05_聚类算法_学习提升+资料推荐-.mp4 [82.9 MB]
02_聚类算法_算法原理_客户价值分析_实践1 集
  • 05_01_聚类算法_算法原理_客户价值分析_实践-.mp4 [240.5 MB]
01_聚类算法_综合实践_客户价值分析_思路1 集
  • 05_01_聚类算法_综合实践_客户价值分析_思路-.mp4 [42.4 MB]
05_聚类算法_综合实践_文本文档分析_实践1 集
  • 05_02_聚类算法_综合实践_文本文档分析_实践-.mp4 [191.1 MB]
04_聚类算法_综合实践_文本文档分析_数据集介绍1 集
  • 05_02_聚类算法_综合实践_文本文档分析_数据集介绍-.mp4 [32.5 MB]
03_聚类算法_综合实践_文本文档分析_思路1 集
  • 05_02_聚类算法_综合实践_文本文档分析_思路-.mp4 [38.0 MB]
第三章 算法优化8 集
  • 03_08_聚类算法_算法优化_小结-.mp4 [14.2 MB]
  • 03_06_聚类算法_算法优化_ISODATA-.mp4 [171.8 MB]
  • 03_02_聚类算法_算法优化_k-means++-.mp4 [53.4 MB]
  • 03_07_聚类算法_算法优化_MiniBatchKmeans-.mp4 [143.6 MB]
  • 03_04_聚类算法_算法优化_Kernel Kmeans-.mp4 [275.7 MB]
  • 03_05_聚类算法_算法优化_K-medoids-.mp4 [184.1 MB]
  • 03_01_聚类算法_算法优化_Canopy配合初始聚类-.mp4 [75.1 MB]
  • 03_03_聚类算法_算法优化_二分kmeans-.mp4 [54.0 MB]
07_聚类算法_算法进阶_SOM聚类1 集
  • 04_05_聚类算法_算法进阶_SOM聚类-.mp4 [200.2 MB]
01_聚类算法_算法进阶_DBSCAN1 集
  • 04_01_聚类算法_算法进阶_DBSCAN-.mp4 [286.5 MB]
10_聚类算法_算法进阶_Kmeans与DBSCAN聚类比较_案例1 集
  • 04_08_聚类算法_算法进阶_Kmeans与DBSCAN聚类比较_案例.flv [33.0 MB]
06_聚类算法_算法进阶_AP聚类1 集
  • 04_04_聚类算法_算法进阶_AP聚类-.mp4 [194.9 MB]
08_聚类算法_算法进阶_谱聚类1 集
  • 04_06_聚类算法_算法进阶_谱聚类-.mp4 [47.6 MB]
03_聚类算法_算法进阶_层次聚类_中1 集
  • 04_02_聚类算法_算法进阶_层次聚类_中-.mp4 [25.0 MB]
02_聚类算法_算法进阶_层次聚类_上1 集
  • 04_02_聚类算法_算法进阶_层次聚类_上-.mp4 [49.0 MB]
11_聚类算法_算法进阶_案例4_kmeans与DBSCAN聚类对比_实践1 集
  • 04_09_聚类算法_算法进阶_案例4_kmeans与DBSCAN聚类对比_实践.flv [179.4 MB]
09_聚类算法_算法进阶_小结1 集
  • 04_07_聚类算法_算法进阶_小结.flv [50.7 MB]
04_聚类算法_算法进阶_层次聚类_下1 集
  • 04_02_聚类算法_算法进阶_层次聚类_下-.mp4 [178.7 MB]
05_聚类算法_算法进阶_MeanShift聚类1 集
  • 04_03_聚类算法_算法进阶_MeanShift聚类-.mp4 [327.9 MB]
第一章 算法原理15 集
  • 01_08_聚类算法_算法原理_汽车工业数据聚类前期预处理_实践-.mp4 [97.2 MB]
  • 01_04_聚类算法_算法原理_算法流程-.mp4 [102.3 MB]
  • 01_10_聚类算法_算法原理_工业车辆聚类_特征工程_实践-.mp4 [90.5 MB]
  • 01_03_聚类算法_算法原理_算法解析-.mp4 [156.0 MB]
  • 01_09_聚类算法_算法原理_工业车辆聚类_预处理实践-.mp4 [124.8 MB]
  • 01_11_聚类算法_效果衡量_肘部法_实践-.mp4 [38.9 MB]
  • 01_07_聚类算法_算法原理_不同数据集的kmeans聚类_实践-.mp4 [62.0 MB]
  • 01_13_聚类算法_算法原理_工业车辆聚类_特征观察_实践-.mp4 [156.9 MB]
  • 01_01_聚类算法_内容设置-.mp4 [26.4 MB]
  • 01_05_聚类算法_算法原理_总结-.mp4 [40.8 MB]
  • 01_12_聚类算法_算法原理_工业车辆聚类_特征选择_实践-.mp4 [60.0 MB]
  • 01_02_聚类算法_算法原理_课题导入-.mp4 [88.1 MB]
  • 01_06_聚类算法_算法原理_不同数据集的kmeans聚类_案例讲解-.mp4 [66.4 MB]
  • 01_15_聚类算法_算法原理_工业车辆聚类_kmeans算法聚类_实践-.mp4 [135.7 MB]
  • 01_14_聚类算法_算法原理_工业车辆聚类_kmeans算法聚类_实践-.mp4 [208.7 MB]
3-2 经典分类结构2 集
  • 01_LeNet5的计算过程详解-.mp4 [30.0 MB]
  • 02_常见网络结构介绍-.mp4 [22.8 MB]
3-1 卷积网络原理6 集
  • 05_多通道的卷积与多卷积核-.mp4 [10.4 MB]
  • 01_卷积网络结构介绍()-.mp4 [11.1 MB]
  • 03_零填充-.mp4 [14.5 MB]
  • 02_默认卷积的运算过程-.mp4 [9.2 MB]
  • 06_全连接层-.mp4 [8.8 MB]
  • 04_过滤器大小与步长-.mp4 [18.5 MB]
3-3 CNN实战2 集
  • 01_作业介绍-.mp4 [8.0 MB]
  • 02_迁移学习-.mp4 [26.6 MB]
1-4 深层神经网络2 集
  • 01_深层神经网络表示-.mp4 [13.9 MB]
  • 02_深层神经网络的反向传播过程-.mp4 [9.3 MB]
1-2 神经网络基础9 集
  • 05_导数计算图与链式法则-.mp4 [23.2 MB]
  • 01_逻辑回归介绍-.mp4 [25.2 MB]
  • 04_导数意义介绍-.mp4 [7.4 MB]
  • 02_逻辑回归损失函数-.mp4 [13.6 MB]
  • 09_总结-.mp4 [13.0 MB]
  • 06_逻辑回归的导数计算图分析以及参数导数-.mp4 [18.4 MB]
  • 07_作业讲解题1：实现sigmoid函数与梯度实现-.mp4 [5.9 MB]
  • 08_作业讲解题2：单神经元神经网络(logistic)分类作业流程介绍-.mp4 [8.7 MB]
  • 03_梯度下降算法过程以及公式-.mp4 [16.9 MB]
1-3 浅层神经网络8 集
  • 04_作业介绍-.mp4 [6.4 MB]
  • 02_浅层神经网络的前向传播-.mp4 [11.1 MB]
  • 07_作业实现：网络模型逻辑实现-.mp4 [16.2 MB]
  • 06_作业实现：反向传播与更新梯度-.mp4 [27.5 MB]
  • 03_浅层神经网络的反向传播-.mp4 [17.4 MB]
  • 08_总结-.mp4 [6.8 MB]
  • 05_作业实现：初始化模型与前向传播-.mp4 [24.0 MB]
  • 01_浅层神经网络表示-.mp4 [13.2 MB]
1-1 深度学习介绍2 集
  • 02_深度学习介绍-.mp4 [26.6 MB]
  • 01_深度学习课程介绍-.mp4 [6.4 MB]
4_1_高级主题12 集
  • 5.01_自动编码器介绍(Av98007795,P5)-.mp4 [8.7 MB]
  • 4.06_生成数字图片案例：运行保存图片并对比(Av98007795,P4)-.mp4 [11.5 MB]
  • 2.04_生成数字图片案例：模型初始化代码编写(Av98007795,P2)-.mp4 [39.6 MB]
  • 1.01_高级主题介绍、GAN介绍(Av98007795,P1)-.mp4 [24.7 MB]
  • 6.02_案例：编码器类别、普通自编码器流程、模型初始化逻辑(Av98007795,P6)-.mp4 [29.7 MB]
  • 8.04_案例：深度自编码器编写演示(Av98007795,P8)-.mp4 [7.3 MB]
  • 13.02_深度学习课程总结(Av98007795,P13)-.mp4 [21.7 MB]
  • 3.05_生成数字图片案例：训练流程(Av98007795,P3)-.mp4 [33.4 MB]
  • 10.06_案例：降噪编码器介绍(Av98007795,P10)-.mp4 [7.9 MB]
  • 7.03_案例：训练普通自编码器(Av98007795,P7)-.mp4 [25.0 MB]
  • 11.07_案例：降噪编码器案例(Av98007795,P11)-.mp4 [13.6 MB]
  • 9.05_案例：卷积自编码器编写演示(Av98007795,P9)-.mp4 [14.1 MB]
05_人脸识别48 集
  • 3_1_1_语音识别_介绍和API-.mp4 [16.7 MB]
  • 2_1_8_人脸检测_性别年龄总结-.mp4 [24.2 MB]
  • 3_1_3_语音识别案例_案例-.mp4 [17.3 MB]
  • 2_2_1_图像识别功能_应用创建-.mp4 [22.0 MB]
  • 2_2_10_定制化图像识别_物体检测_-.mp4 [21.9 MB]
  • 5_1_3_妗堜緥_鑾峰彇token-.mp4 [29.5 MB]
  • 2_1_4_人脸检测_获取access_toke-.mp4 [25.3 MB]
  • 2_1_5_人脸检测_调用API-.mp4 [46.2 MB]
  • 2_1_6_人脸检测_图像坐标-.mp4 [16.9 MB]
  • 0_课程组成和目标-.mp4 [3.5 MB]
  • 3_2_1璇煶鍚堟垚-.mp4 [13.9 MB]
  • 2_2_11_定制化图像识别_物体检测API_错误码-.mp4 [9.3 MB]
  • 2_1_7_人脸检测_边框-.mp4 [26.3 MB]
  • 5_1_1_案例_前端部分介绍.vep-.mp4 [15.2 MB]
  • 3_1_2_语音识别案例_代码浏览-.mp4 [10.8 MB]
  • 2_1_1_人脸识别功能介绍_开通应用-.mp4 [22.6 MB]
  • 1_1_访问入口-.mp4 [12.5 MB]
  • 2_3_4_杞︾墝璇嗗埆-.mp4 [15.4 MB]
  • 2_2_8_定制化图像识别_图像分类_(1)-.mp4 [46.1 MB]
  • 2_2_3_图像检测识别_菜品识别-.mp4 [24.9 MB]
  • 2_1_5_人脸检测_调用API(1)-.mp4 [46.2 MB]
  • 1_7_人工智能平台_访问方式和SD-.mp4 [37.6 MB]
  • 2_3_3_通用文字识别_其他版本函-.mp4 [7.0 MB]
  • 4_1_1_自然语言处理基础技术-.mp4 [25.9 MB]
  • 2_2_6_定制化图像识别_图像分类_-.mp4 [27.8 MB]
  • 2_3_1_功能介绍_创建应用-.mp4 [22.5 MB]
  • 2_2_7_定制化图像识别_图像分类_-.mp4 [12.3 MB]
  • 2_3_5_通用票据识别-.mp4 [33.4 MB]
  • 1_3_百度深度学习平台_介绍-.mp4 [22.9 MB]
  • 1_5_百度人工智能平台_功能介绍-.mp4 [19.7 MB]
  • 2_3_6_自定义模板_步骤-.mp4 [23.9 MB]
  • 1_6_人工智能平台_服务开通-.mp4 [15.4 MB]
  • 2_1_3_人脸检测_步骤和代码浏览-.mp4 [23.8 MB]
  • 2_2_2_图像识别_物体检测API_-.mp4 [32.6 MB]
  • 2_2_9_定制化图像识别_图像分类-.mp4 [11.9 MB]
  • 1_2_机器学习平台_介绍.vep-.mp4 [19.3 MB]
  • 5_1_0_人脸打卡案例_介绍-.mp4 [5.8 MB]
  • 2_3_7_自定义模板_实际创建-.mp4 [19.2 MB]
  • 2_1_7_人脸检测_边框(1)-.mp4 [26.3 MB]
  • 2_3_8_自定义模板_API和代码-.mp4 [17.1 MB]
  • 2_3_2_通用文字识别_代码-.mp4 [32.3 MB]
  • 2_1_2浜鸿劯璇嗗埆_API-.mp4 [35.1 MB]
  • 2_2_8_定制化图像识别_图像分类_-.mp4 [46.1 MB]
  • 2_2_4_图像检测_车辆检测-.mp4 [29.3 MB]
  • 2_2_5_定制化图像识别_特点和功-.mp4 [15.9 MB]
  • 1_4_百度深度学习平台_创建集群-.mp4 [16.0 MB]
  • 5_1_4_案例_添加用户_人脸搜索-.mp4 [47.7 MB]
  • 2_1_9_人脸检测_SDK方式-.mp4 [27.2 MB]
4-2 词嵌入2 集
  • 01_词嵌入介绍-.mp4 [17.8 MB]
  • 02_词嵌入案例-.mp4 [27.2 MB]
4-1 循环神经网络6 集
  • 01_循环神经网络背景介绍-.mp4 [11.2 MB]
  • 03_词的表示与矩阵形状运算-.mp4 [25.8 MB]
  • 05_手写RNN案例：单个cell前向传播-.mp4 [19.3 MB]
  • 02_循环神经网络结构原理-.mp4 [21.4 MB]
  • 06_手写RNN案例：所有cell的前向传播-.mp4 [26.3 MB]
  • 04_梯度消失、案例介绍-.mp4 [14.9 MB]
4-3 seq2seq与Attention机制8 集
  • 03_机器翻译案例：模型参数定义-.mp4 [14.6 MB]
  • 08_机器翻译案例：model中计算attention输出c逻辑函数实现-.mp4 [20.5 MB]
  • 04_机器翻译案例：数据获取以及数据格式转换介绍-.mp4 [14.8 MB]
  • 01_seq2seq介绍与理解-.mp4 [18.8 MB]
  • 07_机器翻译案例：seq2seq的输出层定义-.mp4 [8.4 MB]
  • 05_机器翻译案例：训练逻辑与网络结构介绍-.mp4 [17.9 MB]
  • 02_机器翻译案例：日期格式翻译转换、代码结构介绍-.mp4 [16.0 MB]
  • 06_机器翻译案例：自定义网络seq2seq的编解码器定义-.mp4 [28.5 MB]
2-4 神经网络调参与BN2 集
  • 02_批标准化定义、公式、为什么有效_.mp4 [50.4 MB]
  • 01_神经网络调参数技巧与如何设置参数、如何运行)_.mp4 [15.8 MB]
2-2 梯度下降算法优化6 集
  • 03_RMSProp与Adam原理与学习率递减_.mp4 [14.7 MB]
  • 05_作业讲解1_.mp4 [68.3 MB]
  • 04_作业介绍_.mp4 [9.2 MB]
  • 06_作业讲解2_.mp4 [4.9 MB]
  • 02_指数加权平均_.mp4 [15.5 MB]
  • 01_Mini梯度下降与Batch梯度下降_.mp4 [29.7 MB]
2-3 深度学习正则化2 集
  • 02_Droupout过程与原理理解_.mp4 [29.0 MB]
  • 01_正则化概念、L2正则化与L1正则化_.mp4 [23.0 MB]
2-1 多分类5 集
  • 01_交叉熵损失原理_.mp4 [24.2 MB]
  • 02_案例：Mnist手写数字数据介绍_.mp4 [14.2 MB]
  • 05_调整学习率带来的问题-.mp4 [11.2 MB]
  • 04_案例：添加模型保存、预测_.mp4 [28.5 MB]
  • 03_案例：主网络结构搭建实现_.mp4 [35.9 MB]
13_黑马头条项目_第10天22 集
  • 17_头条项目关注消息通知推送业务说明.mp4 [20.0 MB]
  • 14_头条项目聊天机器人编写.mp4 [36.0 MB]
  • 01_复习.mp4 [21.9 MB]
  • 09_协程库原理.mp4 [24.0 MB]
  • 21_用户关注消息通知推送测试.mp4 [36.3 MB]
  • 10_协程方式运行socketio服务器的方式.mp4 [10.9 MB]
  • 16_调整socketio代码结构与测试.mp4 [15.7 MB]
  • 12_创建socketio服务器编写.mp4 [18.4 MB]
  • 13_使用命令行提取处理端口号.mp4 [11.7 MB]
  • 15_send方法与测试工具的使用.mp4 [15.0 MB]
  • 05_websocket介绍.mp4 [44.5 MB]
  • 04_利用长连接的comet方式说明.mp4 [32.6 MB]
  • 02_即时通讯说明介绍.mp4 [25.6 MB]
  • 22_关于即时通讯的总结.mp4 [24.2 MB]
  • 08_协程介绍.mp4 [22.6 MB]
  • 19_补充flask和socketio代码添加manager使用.mp4 [32.5 MB]
  • 18_socketio提供的manager使用说明.mp4 [30.5 MB]
  • 11_socketio收发数据的方法.mp4 [29.1 MB]
  • 03_HTTP轮询机制说明.mp4 [22.8 MB]
  • 20_解决消息推送接收人身份的问题.mp4 [66.0 MB]
  • 07_socketio服务器创建的方式.mp4 [22.2 MB]
  • 06_socketio介绍.mp4 [29.6 MB]
day09_黑马头条项目_第06天16 集
  • 11_用户个人信息缓存redis数据选型.mp4 [35.2 MB]
  • 02_缓存的背景.mp4 [35.0 MB]
  • 14_头条项目持久保存数据统计数据选型.mp4 [17.9 MB]
  • 10_头条项目缓存设计.mp4 [28.6 MB]
  • 04_缓存的数据内容.mp4 [48.8 MB]
  • 16_扩展_加密算法说明2.mp4 [11.4 MB]
  • 12_用户关注里诶包缓存redis数据选型.mp4 [30.8 MB]
  • 03_缓存架构.mp4 [25.6 MB]
  • 01_复习.mp4 [37.2 MB]
  • 13_头条项目持久保存数据历史数据选型.mp4 [37.9 MB]
  • 09_缓存穿透与缓存雪崩.mp4 [30.5 MB]
  • 06_缓存数据的有效期原因.mp4 [14.1 MB]
  • 08_缓存使用模式.mp4 [45.4 MB]
  • 05_缓存的数据保存形式.mp4 [30.8 MB]
  • 07_缓存的有效期和淘汰策略.mp4 [68.3 MB]
  • 15_扩展_加密算法说明1.mp4 [7.6 MB]
10_黑马头条项目_第07天13 集
  • 08_缓存工具类异常处理的编写.mp4 [43.8 MB]
  • 01_复习.mp4 [23.9 MB]
  • 10_用户个人页视图编写与测试.mp4 [59.0 MB]
  • 11_统计数据持久保存工具类编写.mp4 [58.7 MB]
  • 06_用户个人信息缓存工具类查询代码编写2.mp4 [31.8 MB]
  • 02_缓存工具类的封装设计思路.mp4 [45.5 MB]
  • 03_用户个人信息缓存工具类中属性设计.mp4 [15.9 MB]
  • 09_用户个人信息缓存工具类清除缓存和判断用户存在方法编写.mp4 [30.8 MB]
  • 12_zincrby命令说明.mp4 [10.9 MB]
  • 05_用户个人信息缓存工具类查询代码编写1.mp4 [42.2 MB]
  • 07_缓存有效期工具类的编写.mp4 [42.9 MB]
  • 04_用户个人信息缓存工具类中方法设计.mp4 [17.3 MB]
  • 13_统计工具类的抽象与继承编写.mp4 [23.7 MB]
day6_黑马头条项目11 集
  • 09数据库优化.mp4 [16.6 MB]
  • 集群和分布式.mp4 [14.2 MB]
  • 11redis鎸佷箙鍖朅OF鍜孯DB.mp4 [40.7 MB]
  • 02课程介绍.mp4 [23.9 MB]
  • 08数据库索引.mp4 [16.1 MB]
  • 01反馈和课程回顾.mp4 [30.3 MB]
  • 07分布式id和雪花算法.mp4 [32.1 MB]
  • 12redis数据高可用.mp4 [45.0 MB]
  • 05主从复制和读写分离.mp4 [12.0 MB]
  • 03复制集和分布式.mp4 [14.2 MB]
  • 04redis复制集和分布式说明.mp4 [17.4 MB]
15_黑马头条项目_第12天10 集
  • 07_编写搜索接口的单元测试案例.mp4 [49.9 MB]
  • 06_单元测试中创建flask测试客户端.mp4 [28.6 MB]
  • 10_每日反馈.mp4 [29.9 MB]
  • 02_单元测试说明.mp4 [31.3 MB]
  • 03_assert断言使用.mp4 [18.2 MB]
  • 08_gunicorn使用.mp4 [22.9 MB]
  • 05_flask编写单元测试客户端的使用.mp4 [37.7 MB]
  • 09_supervisor使用.mp4 [65.0 MB]
  • 01_复习.mp4 [25.8 MB]
  • 04_unittest使用.mp4 [14.7 MB]
day4_黑马头条项目11 集
  • 12字段类型和索引设计.mp4 [42.4 MB]
  • 10范式和反范式.mp4 [14.7 MB]
  • 05开发平台gitlib说明和Yapi接口平台.mp4 [10.9 MB]
  • 07外键设计说明.mp4 [22.4 MB]
  • 01反馈和课程回顾.mp4 [24.8 MB]
  • 09文章详情页面.mp4 [44.9 MB]
  • 04开发人员和周期说明.mp4 [23.3 MB]
  • 02课程介绍.mp4 [11.4 MB]
  • 13数据库sql文件说明.mp4 [21.5 MB]
  • 03项目技术架构介绍.mp4 [17.7 MB]
  • 08json类型存储图片.mp4 [17.8 MB]
day01_黑马头条项目10 集
  • 01课程介绍.mp4 [9.5 MB]
  • 10开发服务器运行方式.mp4 [21.0 MB]
  • 05环境配置和依赖文件.mp4 [27.5 MB]
  • 06基本程序实现.mp4 [16.6 MB]
  • 11路由说明和指定请求方法.mp4 [24.6 MB]
  • 07程序参数name说明.mp4 [55.8 MB]
  • 08加载配置信息的三种方式.mp4 [71.4 MB]
  • 03Flask框架的基本介绍.mp4 [20.3 MB]
  • 04框架对比和扩展包介绍.mp4 [26.7 MB]
  • 09run方法参数说明.mp4 [25.4 MB]
12_黑马头条项目_第09天14 集
  • 14_头条项目首页文章列表视图编写.mp4 [94.6 MB]
  • 08_rpc接口文件编译生成python代码.mp4 [29.3 MB]
  • 10_rpc服务器函数代码实现.mp4 [34.5 MB]
  • 04_gRPC介绍与使用方式说明.mp4 [59.4 MB]
  • 01_复习与每日反馈.mp4 [63.4 MB]
  • 06_头条项目首页新闻推荐rpc接口文件编写.mp4 [48.3 MB]
  • 09_rpc服务器编写.mp4 [39.8 MB]
  • 11_rpc客户端编写.mp4 [35.9 MB]
  • 07_protobuf语法说明.mp4 [28.6 MB]
  • 05_头条项目首页新闻推荐rpc接口参数分析.mp4 [41.8 MB]
  • 13_在头条flask项目中定义rpc客户端连接对象.mp4 [29.7 MB]
  • 12_rpc的简易加法案例.mp4 [73.0 MB]
  • 02_http与rpc的对比.mp4 [22.7 MB]
  • 03_rpc的介绍说明.mp4 [41.4 MB]
11_黑马头条项目_第08天13 集
  • 05_apscheduler的执行器与触发器.mp4 [22.9 MB]
  • 08_定时修正统计数据的定时任务编写.mp4 [61.9 MB]
  • 01_复习.mp4 [38.0 MB]
  • 12_web系统与推荐系统调用需求分析.mp4 [27.7 MB]
  • 04_apscheduler的调度器.mp4 [35.2 MB]
  • 03_定时任务的解决方式对比.mp4 [37.8 MB]
  • 11_定时任务方法抽离复用编写2.mp4 [29.6 MB]
  • 10_定时任务方法抽离复用编写1.mp4 [35.7 MB]
  • 13_子系统调用方式说明.mp4 [21.4 MB]
  • 07_头条项目中定义调度器编写.mp4 [39.7 MB]
  • 06_apscheduler的定时任务管理.mp4 [7.6 MB]
  • 09_解决定时任务重需要使用flask上下文对象的问题.mp4 [21.3 MB]
  • 02_修正统计数据的需求分析.mp4 [50.4 MB]
day7_黑马头条项目10 集
  • 11用户登录代码说明.mp4 [25.8 MB]
  • 05项目运行方式演示和说明.mp4 [52.0 MB]
  • 01反馈说明和课程回顾.mp4 [26.3 MB]
  • 06项目目录说明1.mp4 [50.7 MB]
  • 07项目目录说明2.mp4 [20.0 MB]
  • 03读写分离与事务隔离级别.mp4 [16.4 MB]
  • 08项目调试方法和tail命令.mp4 [15.9 MB]
  • 02课程介绍.mp4 [16.1 MB]
  • 04Gitflow工作流和冲突说明.mp4 [30.1 MB]
  • 13请求钩子提取用户id.mp4 [34.7 MB]
day8_黑马头条项目11 集
  • 01反馈和课程回顾.mp4 [15.6 MB]
  • 04token的刷新实现.mp4 [47.1 MB]
  • 06对象存储七牛云介绍.mp4 [22.7 MB]
  • 08七牛云工具封装.mp4 [45.0 MB]
  • 10上传头像接口设计.mp4 [16.2 MB]
  • 02课程介绍.mp4 [11.3 MB]
  • 03登录验证装饰器.mp4 [39.5 MB]
  • 11头像上传实现和测试.mp4 [73.5 MB]
  • 07七牛云实现流程图.mp4 [20.9 MB]
  • 09七牛云工具测试.mp4 [36.0 MB]
  • 12CDN介绍和Yapi接口管理平台.mp4 [24.4 MB]
day3_黑马头条项目12 集
  • 03flask-restful工具的基本使用.mp4 [20.4 MB]
  • 02课程介绍.mp4 [20.3 MB]
  • 08flask-restful请求处理location.mp4 [12.6 MB]
  • 04flask-restful蓝图使用.mp4 [19.7 MB]
  • 13pycharm配置远程解释器.mp4 [57.9 MB]
  • 01反馈和课程回顾.mp4 [31.6 MB]
  • 14产品原型使用说明.mp4 [11.1 MB]
  • 09flask-restful响应处理marshal序列化数据.mp4 [24.1 MB]
  • 11项目课程说明和学习目标.mp4 [23.1 MB]
  • 07flask-restful璇锋眰澶勭悊type.mp4 [26.7 MB]
  • 12虚拟机的基本使用.mp4 [21.8 MB]
  • 10flask-restful响应处理定义json格式数据.mp4 [39.8 MB]
day2_黑马头条项目13 集
  • 02课程介绍.mp4 [27.1 MB]
  • 07作业说明不使用装饰器实现路由映射.mp4 [11.9 MB]
  • 01课程回顾.mp4 [17.2 MB]
  • 14手动开启上下文.mp4 [13.6 MB]
  • 04请求信息自定义转换器.mp4 [30.4 MB]
  • 10寮傚父澶勭悊abort鍜宔rrohandler.mp4 [22.7 MB]
  • 09鐘舵€佷繚鎸乧ookie鍜宻ession.mp4 [33.8 MB]
  • 11璇锋眰閽╁瓙.mp4 [23.3 MB]
  • 08响应信息自定义状态码和响应头.mp4 [15.2 MB]
  • 13用户身份验证g对象.mp4 [18.1 MB]
  • 05请求信息request对象的使用.mp4 [45.1 MB]
  • 03请求信息固定参数转换器.mp4 [35.7 MB]
  • 06响应信息模板&重定向&json.mp4 [41.9 MB]
14_黑马头条项目_第11天23 集
  • 09_类型表保存数据的确定.mp4 [26.4 MB]
  • 01_复习.mp4 [25.0 MB]
  • 14_es数据导入与logstash使用.mp4 [99.1 MB]
  • 11_查询修改删除类型表.mp4 [30.6 MB]
  • 10_类型映射的创建.mp4 [47.0 MB]
  • 20_补全提示建议查询使用.mp4 [30.3 MB]
  • 22_数据库连接查询说明.mp4 [38.6 MB]
  • 04_分析_相关性计算和搜索原理总结.mp4 [34.4 MB]
  • 08_索引库操作.mp4 [18.7 MB]
  • 16_es高级查询使用.mp4 [62.6 MB]
  • 05_es集群说明.mp4 [37.3 MB]
  • 15_es基本查询使用.mp4 [32.8 MB]
  • 12_新增查询文档数据.mp4 [22.0 MB]
  • 21_头条项目用户搜索输入提示补全业务实现.mp4 [42.5 MB]
  • 19_拼写纠错建议查询使用.mp4 [23.9 MB]
  • 06_curl使用与查询集群状态.mp4 [21.7 MB]
  • 23_扩展_TCP三次握手四次挥手说明.mp4 [19.0 MB]
  • 02_elasticsearch说明.mp4 [29.0 MB]
  • 18_头条项目用户文章搜索视图编写.mp4 [73.3 MB]
  • 07_ik中文分析器使用与测试.mp4 [11.7 MB]
  • 13_修改删除文档数据.mp4 [23.5 MB]
  • 03_反向索引.mp4 [25.6 MB]
  • 17_python使用es的库.mp4 [13.3 MB]
day5_黑马头条项目11 集
  • 16SQLAlchemy更新删除事务.mp4 [17.4 MB]
  • 15SQLAlchemy连接查询2.mp4 [80.4 MB]
  • 13SQLAlchemy优化查询和聚合查询.mp4 [36.6 MB]
  • 12SQLAlchemy运算符与或非order_by&limit&offset&count&复合查询.mp4 [46.4 MB]
  • 02课程介绍.mp4 [6.5 MB]
  • 01课程回顾.mp4 [13.0 MB]
  • 06SQLALchemy基本配置.mp4 [29.0 MB]
  • 09SQLAlchemy添加数据.mp4 [19.7 MB]
  • 14SQLAlchemy连接查询1.mp4 [54.6 MB]
  • 08SQLAlchemy模型类定义和关系说明.mp4 [44.6 MB]
  • 07SQLAlchemy的字段列选项关系选项.mp4 [23.3 MB]
Git篇54 集
  • 010_git快速入门之环境初始化(命令简介+梳理)-.mp4 [37.3 MB]
  • 046_git快速入门之git远程仓库管理(其他+梳理)-.mp4 [16.9 MB]
  • 036_git快速入门之忽略实践(全局.gitignore)-.mp4 [18.5 MB]
  • 014_git快速入门之区域管理(区域简介+区域设置)-.mp4 [23.7 MB]
  • 051_git快速入门之标签管理(基本操作)-.mp4 [53.0 MB]
  • 025_git快速入门之文件级别撤销(简介+撤销提交)-.mp4 [26.1 MB]
  • 009_git快速入门之环境初始化(克隆仓库+命令补全)-.mp4 [37.5 MB]
  • 018_git快速入门之基础操作(区域操作简介)-.mp4 [31.5 MB]
  • 005_git快速入门之git安装(简介+目录标准化+依赖软件)-.mp4 [39.9 MB]
  • 007_git快速入门之git安装(windows安装+梳理)-.mp4 [30.1 MB]
  • 021_git快速入门之文件区别(命令简介+4场景实践)-.mp4 [38.6 MB]
  • 000_课程简介(强烈推荐观看,画好知识边界)-.mp4 [24.3 MB]
  • 039_git快速入门之远程仓库简介(简介+分类+命令)-.mp4 [21.2 MB]
  • 041_git快速入门之git远程仓库(查看+创建)-.mp4 [43.0 MB]
  • 013_git快速入门之数据结构(数据结构实践2+梳理)-.mp4 [22.8 MB]
  • 015_git快速入门之文件状态(状态简介+状态详解)-.mp4 [18.2 MB]
  • 045_git快速入门之git远程仓库管理(添加+获取+提交)-.mp4 [34.1 MB]
  • 026_git快速入门之文件级别撤销(撤销提交+撤销缓存)-.mp4 [34.5 MB]
  • 012_git快速入门之数据结构(数据结构实践1)-.mp4 [42.5 MB]
  • 053_git进阶之分支基础(前置知识)-.mp4 [15.8 MB]
  • 037_git快速入门之忽略实践(忽略失效)-.mp4 [30.5 MB]
  • 044_git快速入门之git远程仓库部署(权限配置+测试)-.mp4 [31.4 MB]
  • 033_git快速入门之忽略基础(方法+原则+优先级)-.mp4 [45.1 MB]
  • 011_git快速入门之数据结构(基本结构+对象数据库)-.mp4 [27.1 MB]
  • 048_git快速入门之标签管理(基础简介+日常命令)-.mp4 [45.7 MB]
  • 031_git快速入门之对象级别撤销(revert实践)-.mp4 [31.5 MB]
  • 002_git快速入门之基础知识(git历史)-.mp4 [42.5 MB]
  • 016_git快速入门之文件状态实践(状态实践)-.mp4 [33.4 MB]
  • 038_git快速入门之基础操作(小结)-.mp4 [44.3 MB]
  • 029_git快速入门之对象级别撤销(简介+reset原理)-.mp4 [27.4 MB]
  • 040_git快速入门之git远程仓库(简介+4种协议)-.mp4 [50.2 MB]
  • 035_git快速入门之忽略实践(项目.gitignore)-.mp4 [24.6 MB]
  • 032_git快速入门之对象级别撤销(reflog+check实践)-.mp4 [36.9 MB]
  • 023_git快速入门之增加&提交(补充技巧知识点)-.mp4 [25.8 MB]
  • 042_git快速入门之git远程仓库部署(简介+基本环境)-.mp4 [22.5 MB]
  • 027_git快速入门之文件级别撤销(撤销修改)-.mp4 [39.9 MB]
  • 017_git快速入门之文件状态实践(小结)-.mp4 [20.9 MB]
  • 034_git快速入门之忽略实践(exclude)-.mp4 [18.6 MB]
  • 022_git快速入门之删除&移动(2删除+2移动)-.mp4 [42.4 MB]
  • 049_git快速入门之标签管理(认证标签简介+原理简介)-.mp4 [32.7 MB]
  • 028_git快速入门之文件级别撤销(梳理)-.mp4 [31.7 MB]
  • 050_git快速入门之标签管理(生成秘钥)-.mp4 [41.5 MB]
  • 047_git快速入门之git远程仓库(小结)-.mp4 [15.2 MB]
  • 001_git快速入门之基础知识(版本控制回顾)-.mp4 [35.2 MB]
  • 008_git快速入门之环境初始化(初始化+配置实践)-.mp4 [46.7 MB]
  • 043_git快速入门之git远程仓库部署(网络环境配置)-.mp4 [37.4 MB]
  • 006_git快速入门之git安装(源码方式安装)-.mp4 [30.4 MB]
  • 030_git快速入门之对象级别撤销(reset实践)-.mp4 [31.2 MB]
  • 004_git快速入门之基础知识(小结)-.mp4 [13.0 MB]
  • 003_git快速入门之基础知识(git生态)-.mp4 [18.4 MB]
  • 019_git快速入门之基础操作(获取操作)-.mp4 [28.6 MB]
  • 024_git快速入门之提交记录(简介+参数)-.mp4 [69.4 MB]
  • 052_git快速入门之标签管理(小结)-.mp4 [21.4 MB]
  • 020_git快速入门之增加&提交(增加+提交+修改后提交)-.mp4 [43.8 MB]
08RPC实现之消息协议转换实现9 集
  • 083_请求消息数据转换为请求原始参数的实现2-.mp4 [22.7 MB]
  • 086_请求消息协议实现测试-.mp4 [13.0 MB]
  • 089_消息协议实现总结-.mp4 [2.5 MB]
  • 081_请求参数转换为消息数据实现-.mp4 [22.6 MB]
  • 082_请求消息数据转换为请求原始参数的实现1-.mp4 [4.0 MB]
  • 084_args_decode方法修正与read_all方法实现-.mp4 [15.2 MB]
  • 085_方法名协议实现-.mp4 [9.4 MB]
  • 087_返回值数据转换为消息数据的实现-.mp4 [15.0 MB]
  • 088_消息数据转换为返回值数据的实现-.mp4 [10.0 MB]
10RPC完整实现7 集
  • 101_实现思路说明-.mp4 [3.4 MB]
  • 105_Server补充实现-.mp4 [21.8 MB]
  • 107_RPC调用测试-.mp4 [8.5 MB]
  • 102_ClientStub实现-.mp4 [23.8 MB]
  • 103_ServerStub实现1-.mp4 [32.4 MB]
  • 104_ServerStub实现2-.mp4 [30.6 MB]
  • 106_服务器与客户端调用案例实现-.mp4 [13.7 MB]
02RFC原理课程内容说明1 集
  • 02_第一部分RPC原理课程内容说明-.mp4 [1.7 MB]
06RPC实现之消息协议设计3 集
  • 061_消息协议实现思路与divide调用参数确定-.mp4 [13.8 MB]
  • 063_返回消息协议设计-.mp4 [7.5 MB]
  • 062_调用请求消息协议设计-.mp4 [13.8 MB]
04RPC结构和调用流程1 集
  • 04_RPC结构和调用流程-.mp4 [16.6 MB]
09RPC传输控制实现3 集
  • 091_RPC传输协议说明-.mp4 [10.6 MB]
  • 093_服务端传输工具实现-.mp4 [5.6 MB]
  • 092_客户端传输工具实现-.mp4 [5.5 MB]
07struct模块使用说明1 集
  • 07_struct模块使用说明-.mp4 [9.9 MB]
01整体课程介绍1 集
  • 01_课程整体介绍及前置知识点说明-.mp4 [3.5 MB]
03RPC介绍3 集
  • 033_RPC的优缺点-.mp4 [6.4 MB]
  • 031_RPC简介背景和用途-.mp4 [10.3 MB]
  • 032_RPC在广义和狭义上的理解及与HTTP的关系-.mp4 [11.5 MB]
11多线程RPC服务器实现1 集
  • 11_多线程RPC服务器实现-.mp4 [14.0 MB]
05RPC消息协议4 集
  • 053_消息边界问题说明-.mp4 [14.2 MB]
  • 054_消息内容和压缩问题-.mp4 [16.8 MB]
  • 052_设计消息协议的目标-.mp4 [5.6 MB]
  • 051_消息协议的说明-.mp4 [5.8 MB]
05OpenStack综合实践之总结1 集
  • 093_OpenStack综合实践之总结-.mp4 [20.9 MB]
04OpenStack综合实践之深入理解VM8 集
  • 085_OpenStack综合实践之深入理解VM(VM实例-实例文件)-.mp4 [32.9 MB]
  • 084_OpenStack综合实践之深入理解VM(如何通网)-.mp4 [17.6 MB]
  • 090_OpenStack综合实践之深入理解VM(流程详解-第2阶段)-.mp4 [30.3 MB]
  • 089_OpenStack综合实践之深入理解VM(流程详解-第1阶段)-.mp4 [23.8 MB]
  • 091_OpenStack综合实践之深入理解VM(流程详解-梳理)-.mp4 [40.1 MB]
  • 092_OpenStack综合实践之深入理解VM(小结)-.mp4 [26.9 MB]
  • 087_OpenStack综合实践之深入理解VM(属性获取-元数据+获取)-.mp4 [25.3 MB]
  • 086_OpenStack综合实践之深入理解VM(VM实例-配置文件)-.mp4 [20.3 MB]
03OpenStack综合实践之块存储部署15 集
  • 079_OpenStack综合实践之块存储部署(nfs存储部署-nfs后端+效果)-.mp4 [29.0 MB]
  • 072_OpenStack综合实践之块存储部署(控制服务部署-配置2+数据同步+权限+效果)-.mp4 [38.0 MB]
  • 069_OpenStack综合实践之块存储部署(简介-官方+存储+cinder)-.mp4 [25.9 MB]
  • 080_OpenStack综合实践之块存储部署(nfs存储部署-实践+梳理)-.mp4 [16.0 MB]
  • 071_OpenStack综合实践之块存储部署(控制服务部署-数据库+软件+配置)-.mp4 [25.1 MB]
  • 076_OpenStack综合实践之块存储部署(存储实践-创建+附加)-.mp4 [24.8 MB]
  • 083_OpenStack综合实践之块存储部署(总结)-.mp4 [36.0 MB]
  • 074_OpenStack综合实践之块存储部署(存储服务部署-软件+配置)-.mp4 [28.1 MB]
  • 078_OpenStack综合实践之块存储部署(nfs存储部署-流程+磁盘+nfs)-.mp4 [14.9 MB]
  • 073_OpenStack综合实践之块存储部署(存储服务部署-磁盘+lvm配置)-.mp4 [25.6 MB]
  • 075_OpenStack综合实践之块存储部署(存储服务部署-效果+梳理)-.mp4 [14.1 MB]
  • 077_OpenStack综合实践之块存储部署(存储实践-卸载+删除+梳理)-.mp4 [26.3 MB]
  • 081_OpenStack综合实践之块存储部署(多存储部署-准备+多存储配置+前后端绑定)-.mp4 [29.2 MB]
  • 070_OpenStack综合实践之块存储部署(组件详解-流程+组件+场景)-.mp4 [24.1 MB]
  • 082_OpenStack综合实践之块存储部署(多存储实践-命令行+可视化界面)-.mp4 [27.2 MB]
02OpenStack综合实践之可视化界面8 集
  • 064_OpenStack综合实践之可视化界面(管理员界面-项目)-.mp4 [26.7 MB]
  • 063_OpenStack综合实践之可视化界面(部署-效果+梳理)-.mp4 [12.9 MB]
  • 068_OpenStack综合实践之可视化界面(小结)-.mp4 [12.0 MB]
  • 062_OpenStack综合实践之可视化界面(部署-软件+配置)-.mp4 [34.1 MB]
  • 066_OpenStack综合实践之可视化界面(管理员界面-身份管理+梳理)-.mp4 [18.6 MB]
  • 067_OpenStack综合实践之可视化界面(操作员界面)-.mp4 [10.4 MB]
  • 061_OpenStack综合实践之可视化界面(简介)-.mp4 [15.5 MB]
  • 065_OpenStack综合实践之可视化界面(管理员界面-管理员)-.mp4 [22.3 MB]
01OpenStack综合实践之VM创建8 集
  • 060_OpenStack综合实践之VM创建(小结)-.mp4 [16.1 MB]
  • 058_OpenStack综合实践之VM创建(常见报错3)-.mp4 [30.3 MB]
  • 053_OpenStack综合实践之VM创建(实例属性-网络+子网+实例)-.mp4 [31.0 MB]
  • 059_OpenStack综合实践之VM创建(排错思路)-.mp4 [19.3 MB]
  • 055_OpenStack综合实践之VM创建(创建实例-创建+检查)-.mp4 [29.0 MB]
  • 054_OpenStack综合实践之VM创建(创建实例-秘钥+安全组+检查)-.mp4 [20.8 MB]
  • 056_OpenStack综合实践之VM创建(常见报错1)-.mp4 [30.2 MB]
  • 057_OpenStack综合实践之VM创建(常见报错2)-.mp4 [22.1 MB]
01课程简介1 集
  • 000_课程简介-.mp4 [4.5 MB]
04版本控制4 集
  • 012_版本控制之简介(版本控制)-.mp4 [22.3 MB]
  • 013_版本控制之简介(版本控制作用)-.mp4 [23.7 MB]
  • 014_版本控制之种类(分类和工具)-.mp4 [29.1 MB]
  • 015_版本控制之总结-.mp4 [6.4 MB]
02绪论1 集
  • 001_绪论(强烈推荐观看,画好知识边界)-.mp4 [29.0 MB]
06开发模型12 集
  • 035_开发模型之敏捷模型2-.mp4 [21.5 MB]
  • 033_开发模型之螺旋模型-.mp4 [26.4 MB]
  • 039_代码配置管理上篇总结-.mp4 [19.4 MB]
  • 029_开发模型之瀑布模型-.mp4 [36.0 MB]
  • 028_开发模型之边做边改-.mp4 [17.8 MB]
  • 038_开发模型之总结-.mp4 [19.4 MB]
  • 032_开发模型之快速原型模型-.mp4 [30.0 MB]
  • 037_开发模型之精益模型2-.mp4 [34.8 MB]
  • 036_开发模型之精益模型1-.mp4 [31.8 MB]
  • 030_开发模型之迭代模型-.mp4 [29.7 MB]
  • 034_开发模型之敏捷模型1-.mp4 [40.2 MB]
  • 031_开发模型之增量模型-.mp4 [33.1 MB]
05分支管理12 集
  • 023_分支管理之主干开发(分支发布)-.mp4 [33.2 MB]
  • 019_分支管理之基础知识(小结)-.mp4 [10.9 MB]
  • 027_分支管理之总结-.mp4 [18.2 MB]
  • 025_分支管理之主干开发(优秀案例)-.mp4 [20.2 MB]
  • 021_分支管理之分支开发(主干发布)-.mp4 [39.1 MB]
  • 017_分支管理之基础知识(分支概念)-.mp4 [34.6 MB]
  • 020_分支管理之分支开发(分支发布)-.mp4 [30.9 MB]
  • 022_分支管理之分支开发(小结)-.mp4 [6.1 MB]
  • 026_分支管理之主干开发(小结)-.mp4 [9.9 MB]
  • 018_分支管理之基础知识(分支开发流程)-.mp4 [28.9 MB]
  • 024_分支管理之主干开发(主干发布)-.mp4 [33.7 MB]
  • 016_分支管理之基础知识(常见术语)-.mp4 [31.4 MB]
03项目基础知识10 集
  • 010_项目基础知识之项目演变(企业中后期两阶段+小结)-.mp4 [21.8 MB]
  • 007_项目基础知识之项目演变(基本结构+开发框架演变)-.mp4 [31.9 MB]
  • 005_项目基础知识之新型生命周期(常见术语)-.mp4 [24.3 MB]
  • 002_项目基础知识之传统生命周期(调研-设计-开发)-.mp4 [23.7 MB]
  • 003_项目基础知识之传统生命周期(测试-运营)-.mp4 [23.5 MB]
  • 008_项目基础知识之项目演变(企业初期四阶段)-.mp4 [34.5 MB]
  • 004_项目基础知识之新型生命周期(项目阶段)-.mp4 [28.5 MB]
  • 011_项目基础知识之总结-.mp4 [18.8 MB]
  • 009_项目基础知识之项目演变(企业中期四阶段)-.mp4 [40.0 MB]
  • 006_项目基础知识之新型生命周期(周期效果+小结)-.mp4 [23.7 MB]
02OpenStack部署之支撑性服务4 集
  • 022_OpenStack部署之支撑性服务(小结)-.mp4 [6.9 MB]
  • 020_OpenStack部署之支撑性服务(rabbitmq-作用+官方介绍+软件+配置+插件)-.mp4 [37.9 MB]
  • 021_OpenStack部署之支撑性服务(memcache-作用+官方介绍+软件+配置)-.mp4 [15.5 MB]
  • 019_OpenStack部署之支撑性服务(数据库-官方介绍+软件+配置+初始化)-.mp4 [27.3 MB]
07OpenStack部署之小结1 集
  • 052_OpenStack部署之(小结)-.mp4 [13.4 MB]
04OpenStack部署之镜像组件5 集
  • 029_OpenStack部署之镜像组件(组件详解-官方+详解+存储+简介+配置)-.mp4 [39.1 MB]
  • 031_OpenStack部署之镜像组件(组件部署-初始化+权限配置)-.mp4 [38.1 MB]
  • 032_OpenStack部署之镜像组件(效果查看)-.mp4 [31.4 MB]
  • 030_OpenStack部署之镜像组件(组件部署-数据库配置+软件安装+软件配置)-.mp4 [36.3 MB]
  • 033_OpenStack部署之镜像组件(小结)-.mp4 [22.5 MB]
03OpenStack部署之认证组件6 集
  • 028_OpenStack部署之认证组件(总结)-.mp4 [26.5 MB]
  • 026_OpenStack部署之认证组件(组件部署-权限配置2+认证效果)-.mp4 [35.5 MB]
  • 023_OpenStack部署之认证组件(组件详解-官方介绍+功能+核心术语+配置)-.mp4 [34.1 MB]
  • 027_OpenStack部署之认证组件(部署梳理)-.mp4 [24.6 MB]
  • 024_OpenStack部署之认证组件(组件部署-数据库配置+软件安装+软件配置+数据同步)-.mp4 [32.7 MB]
  • 025_OpenStack部署之认证组件(组件部署-admin权限+http配置+权限配置1)-.mp4 [27.9 MB]
01OpenStack部署之实验环境5 集
  • 014_OpenStack部署之实验环境(准备工作-Centos7安装)-.mp4 [30.1 MB]
  • 018_OpenStack部署之实验环境(小结)-.mp4 [14.5 MB]
  • 015_OpenStack部署之实验环境(准备工作-ip设置+软件源)-.mp4 [31.2 MB]
  • 016_OpenStack部署之实验环境(准备工作-网络配置+安全配置+主机名配置)-.mp4 [34.1 MB]
  • 017_OpenStack部署之实验环境(基本环境-软件+时间同步+计算节点)-.mp4 [43.7 MB]
06OpenStack部署之网络组件10 集
  • 047_OpenStack部署之网络组件(控制节点部署-权限配置+效果查看)-.mp4 [29.8 MB]
  • 049_OpenStack部署之网络组件(计算节点部署-软件+配置)-.mp4 [24.6 MB]
  • 050_OpenStack部署之网络组件(计算节点部署-效果查看+梳理)-.mp4 [14.7 MB]
  • 043_OpenStack部署之网络组件(组件介绍-官方+原理+组件)-.mp4 [25.2 MB]
  • 045_OpenStack部署之网络组件(控制节点部署-配置2)-.mp4 [27.7 MB]
  • 044_OpenStack部署之网络组件(控制节点部署-数据库+软件+配置1)-.mp4 [31.0 MB]
  • 048_OpenStack部署之网络组件(控制节点部署-梳理)-.mp4 [18.9 MB]
  • 042_OpenStack部署之网络组件(网络简介-简介+功能+基本架构+类型)-.mp4 [33.6 MB]
  • 051_OpenStack部署之网络组件(小结)-.mp4 [25.0 MB]
  • 046_OpenStack部署之网络组件(控制节点部署-配置3+数据同步-.mp4 [18.1 MB]
05OpenStack部署之计算组件7 集
  • 040_OpenStack部署之计算组件(计算组件部署-效果查看)-.mp4 [22.7 MB]
  • 036_OpenStack部署之计算组件(控制组件部署-数据库+软件安装+配置修改1)-.mp4 [50.1 MB]
  • 034_OpenStack部署之计算组件(组件详解-官方+原理+组件)-.mp4 [36.5 MB]
  • 039_OpenStack部署之计算组件(计算组件部署-软件+配置修改+启动)-.mp4 [38.6 MB]
  • 035_OpenStack部署之计算组件(组件详解-权重+梳理)-.mp4 [32.1 MB]
  • 038_OpenStack部署之计算组件(控制组件部署-权限配置+效果查看)-.mp4 [34.5 MB]
  • 041_OpenStack部署之计算组件(小结)-.mp4 [30.7 MB]
01分布式RPC课程知识内容说明1 集
  • 01分布式RPC课程知识内容说明-.mp4 [1.8 MB]
04ZooKeeper安装1 集
  • 04_ZooKeeper安装-.mp4 [38.4 MB]
06RPC服务器程序改写2 集
  • 062_服务器程序改写实现-.mp4 [19.9 MB]
  • 061_保存在zookeeper节点层次和类型的设计确定-.mp4 [9.5 MB]
03认识ZooKeeper2 集
  • 032_ZooKeeper概念说明-.mp4 [28.6 MB]
  • 031_ZooKeeper简介-.mp4 [14.7 MB]
05kazoo使用4 集
  • 051_kazoo简介与安装-.mp4 [2.9 MB]
  • 054_获取节点数据-.mp4 [5.8 MB]
  • 053_创建节点-.mp4 [12.2 MB]
  • 052_客户端连接-.mp4 [3.5 MB]
02分布式系统基础知识2 集
  • 022_分布式系统需要解决的问题与解决方案-.mp4 [9.8 MB]
  • 021_单机部署的缺点和多台服务器分布式的好处-.mp4 [7.3 MB]
07RPC客户端程序改写4 集
  • 072_客户端程序实现1-.mp4 [15.9 MB]
  • 072_客户端程序实现2-.mp4 [7.8 MB]
  • 071_客户端程序改写思路-.mp4 [7.9 MB]
  • 073_测试分布式RPC-.mp4 [7.1 MB]
03Thrift框架的实现技术架构1 集
  • 03_Thrift框架的实现技术架构-.mp4 [6.0 MB]
08客户端案例程序编写2 集
  • 081_客户端调用的工具创建-.mp4 [9.5 MB]
  • 082_客户端调用编写与测试-.mp4 [11.8 MB]
02IDL接口定义语言说明与Thrift使用方法1 集
  • 02_IDL接口定义语言说明与Thrift使用方法-.mp4 [23.6 MB]
01Thrift框架课程知识说明与Thrift简介1 集
  • 01_第三部分Thrift框架课程知识说明与Thrift简介-.mp4 [13.6 MB]
06消息协议与传输的选择1 集
  • 06_消息协议与传输的选择-.mp4 [9.7 MB]
05Thrift接口定义语言4 集
  • 053_注释和服务定义-.mp4 [13.7 MB]
  • 051_基本数据类型与容器类型-.mp4 [10.2 MB]
  • 054_thrift编译器生成代码-.mp4 [11.8 MB]
  • 052_常量枚举结构体与异常类型-.mp4 [10.8 MB]
04Thrift的安装1 集
  • 04_Thrift的安装-.mp4 [15.3 MB]
07服务端案例程序编写3 集
  • 072_服务端接口服务方法实现-.mp4 [12.0 MB]
  • 073_创建服务器开启RPC服务-.mp4 [15.4 MB]
  • 071_服务端程序编写思路-.mp4 [7.9 MB]
02OpenStack实践拓展之定制网络6 集
  • 108_OpenStack实践拓展之定制网络(定制双网络-配置修改+环境检查)-.mp4 [23.5 MB]
  • 106_OpenStack实践拓展之定制网络(双网络-需求+分析+方案)-.mp4 [19.1 MB]
  • 109_OpenStack实践拓展之定制网络(定制双网络-双网络属性+测试)-.mp4 [24.9 MB]
  • 110_OpenStack实践拓展之定制网络(操作梳理)-.mp4 [16.2 MB]
  • 111_OpenStack实践拓展之定制网络(小结)-.mp4 [13.6 MB]
  • 107_OpenStack实践拓展之定制网络(定制双网络-双网卡环境)-.mp4 [25.7 MB]
04OpenStack云计算课程总结2 集
  • 119_OpenStack云计算(入门篇-快速梳理)-.mp4 [38.2 MB]
  • 120_OpenStack云计算(收尾)-.mp4 [7.9 MB]
01OpenStack实践拓展之定制映像11 集
  • 099_OpenStack实践拓展之定制映像(映像制作-脚本框架)-.mp4 [12.2 MB]
  • 097_OpenStack实践拓展之定制映像(映像制作-虚拟机基本安全)-.mp4 [22.8 MB]
  • 105_OpenStack实践拓展之定制映像(小结)-.mp4 [16.9 MB]
  • 094_OpenStack实践拓展之定制映像(映像简介)-.mp4 [16.9 MB]
  • 100_OpenStack实践拓展之定制映像(映像制作-定制脚本1)-.mp4 [15.8 MB]
  • 103_OpenStack实践拓展之定制映像(映像制作-创建vm)-.mp4 [21.1 MB]
  • 096_OpenStack实践拓展之定制映像(映像制作-创建虚拟机)-.mp4 [24.3 MB]
  • 104_OpenStack实践拓展之定制映像(映像制作-效果查看+梳理)-.mp4 [13.3 MB]
  • 095_OpenStack实践拓展之定制映像(映像制作-准备环境)-.mp4 [17.3 MB]
  • 102_OpenStack实践拓展之定制映像(映像制作-其他功能+镜像压缩)-.mp4 [21.4 MB]
  • 101_OpenStack实践拓展之定制映像(映像制作-定制脚本2)-.mp4 [27.5 MB]
03OpenStack实践拓展之其他内容7 集
  • 116_OpenStack实践拓展之其他内容(增加计算节点-梳理)-.mp4 [21.6 MB]
  • 112_OpenStack实践拓展之其他内容(防火墙规则)-.mp4 [15.6 MB]
  • 113_OpenStack实践拓展之其他内容(主机名规则)-.mp4 [18.7 MB]
  • 114_OpenStack实践拓展之其他内容(增加计算节点-需求+环境+部署nova)-.mp4 [47.4 MB]
  • 115_OpenStack实践拓展之其他内容(增加计算节点-部署neutron+测试)-.mp4 [37.8 MB]
  • 118_OpenStack实践拓展之其他内容(小结)-.mp4 [19.9 MB]
  • 117_OpenStack实践拓展之其他内容(删除计算节点)-.mp4 [30.1 MB]
00课程介绍1 集
  • 000_课程简介-.mp4 [20.2 MB]
01绪论1 集
  • 001_绪论(强烈建议观看-知识的边界)-.mp4 [26.0 MB]
12OpenStack简介之实验环境1 集
  • 012_OpenStack简介之实验环境(学习环境+主机环境)-.mp4 [26.3 MB]
13OpenStack简介之小结1 条
  • 013_OpenStack简介之小结-.pcwlenv [22.4 MB]
10OpenStack简介之架构设计1 集
  • 010_OpenStack简介之架构设计(逻辑图+架构设计图+概念图)-.mp4 [32.9 MB]
05云计算基础之常见种类1 集
  • 005_云计算基础之常见种类(云计算分类+衍生云+选用标准)-.mp4 [26.9 MB]
07云计算基础之虚拟化VS云计算1 条
  • 007_云计算基础之虚拟化&云计算(虚拟化+云计算+关系)-.pcwlenv [17.6 MB]
11OpenStack简介之组件介绍1 集
  • 011_OpenStack简介之组件介绍(组件简介+完美组件)-.mp4 [21.8 MB]
02云计算基础之引言1 集
  • 002_云计算基础之引言(资源使用+资源管理+虚拟化+云计算+云计算历史)-.mp4 [40.5 MB]
03云计算基础之基本概念1 集
  • 003_云计算基础之基本概念(云计算概念+什么是云计算)-.mp4 [22.9 MB]
08云计算基础之小结1 集
  • 008_云计算基础之小结-.mp4 [16.2 MB]
004_云计算基础之基本概念(实现方式+现状+提供商)1 集
  • 004_云计算基础之基本概念(实现方式+现状+提供商)-.mp4 [28.2 MB]
09OpenStack简介1 集
  • 009_OpenStack简介之简介(历史+简介+核心服务+发行+使用标准)-.mp4 [36.1 MB]
06云计算基础之基本架构1 集
  • 006_云计算基础之基本架构(基本架构+架构思考)-.mp4 [31.2 MB]
06DR实践8 集
  • 028_lvs快速入门之DR实践(前置知识-ARP表+交换机原理+地址冲突)-.mp4 [38.4 MB]
  • 033_lvs快速入门之DR实践(简单实践-案例实践3)-.mp4 [13.8 MB]
  • 032_lvs快速入门之DR实践(简单实践-案例实践2)-.mp4 [25.8 MB]
  • 031_lvs快速入门之DR实践(简单实践-案例实践1)-.mp4 [34.1 MB]
  • 029_lvs快速入门之DR实践(DR模型-模型简介+模型分析)-.mp4 [20.0 MB]
  • 034_lvs快速入门之DR实践(原理详解)-.mp4 [16.0 MB]
  • 035_lvs快速入门之DR实践(应用技巧)-.mp4 [24.3 MB]
  • 030_lvs快速入门之DR实践(简单实践-案例需求+需求分析+技术点分析)-.mp4 [20.2 MB]
01集群简介4 集
  • 002_集群基础之集群简介(集群类型-实现方式)-.mp4 [28.1 MB]
  • 001_集群基础之集群简介(集群基础-场景需求+解决方案+访问流程)-.mp4 [25.0 MB]
  • 000_课程概况-.mp4 [4.4 MB]
  • 003_集群基础之集群简介(小结)-.mp4 [6.2 MB]
03LVS快速入门5 集
  • 009_lvs快速入门之lvs快速入门(规则命令-保存+清空+载入+服务)-.mp4 [45.5 MB]
  • 006_lvs快速入门之lvs快速入门(安装软件-命令简介)-.mp4 [30.1 MB]
  • 008_lvs快速入门之lvs快速入门(主机命令-查看+增加+编辑+删除)-.mp4 [37.2 MB]
  • 007_lvs快速入门之lvs快速入门(集群命令-查看+增加+编辑+删除)-.mp4 [26.8 MB]
  • 010_lvs快速入门之lvs快速入门(小结)-.mp4 [13.5 MB]
04NAT实践13 集
  • 013_lvs快速入门之NAT实践(简单实践-案例需求+需求分析+关键点分析)-.mp4 [24.3 MB]
  • 012_lvs快速入门之NAT实践(NAT简介-模型简介+模型分析)-.mp4 [23.3 MB]
  • 023_lvs快速入门之NAT实践(小结)-.mp4 [20.2 MB]
  • 021_lvs快速入门之NAT实践(进阶实践2-https实践)-.mp4 [27.3 MB]
  • 018_lvs快速入门之NAT实践(进阶实践-场景需求+需求分析+关键点分析+实践)-.mp4 [34.3 MB]
  • 017_lvs快速入门之NAT实践(应用技巧-原理技巧+应用技巧)-.mp4 [30.0 MB]
  • 014_lvs快速入门之NAT实践(简单实践-案例需求+基础环境设置)-.mp4 [21.5 MB]
  • 020_lvs快速入门之NAT实践(进阶实践2-场景需求+需求分析+关键点分析+实践)-.mp4 [23.0 MB]
  • 022_lvs快速入门之NAT实践(进阶实践2-集群实践+小结)-.mp4 [12.1 MB]
  • 016_lvs快速入门之NAT实践(原理详解-流程详解+数据包详解+请求流程)-.mp4 [27.9 MB]
  • 015_lvs快速入门之NAT实践(简单实践-web服务+lvs集群设置)-.mp4 [31.5 MB]
  • 019_lvs快速入门之NAT实践(进阶实践1-实践小结+数据包分析)-.mp4 [25.2 MB]
  • 011_lvs快速入门之NAT实践(前置知识-网络设备+基本环境)-.mp4 [25.6 MB]
02LVS基础2 集
  • 004_lvs快速入门之lvs基础(防火墙回顾-五表五链+应用场景+地址转换)-.mp4 [23.6 MB]
  • 005_lvs快速入门之lvs基础(简介-结构)-.mp4 [55.2 MB]
05调度策略4 集
  • 025_lvs快速入门之调度策略(调度基础+静态方法+动态方法)-.mp4 [35.0 MB]
  • 026_lvs快速入门之调度策略(wrr实践)-.mp4 [18.3 MB]
  • 024_lvs快速入门之调度策略(前置知识-代理+会话+hash)-.mp4 [26.8 MB]
  • 027_lvs快速入门之调度策略(sh实践)-.mp4 [12.8 MB]
07TUN实践8 集
  • 038_lvs快速入门之TUN实践(隧道实践)-.mp4 [51.3 MB]
  • 039_lvs快速入门之TUN实践(TUN简介)-.mp4 [16.8 MB]
  • 044_lvs快速入门之小结-.mp4 [20.9 MB]
  • 037_lvs快速入门之TUN实践(前置知识2)-.mp4 [9.9 MB]
  • 042_lvs快速入门之TUN实践(简单实践3)-.mp4 [27.0 MB]
  • 041_lvs快速入门之TUN实践(简单实践2)-.mp4 [28.7 MB]
  • 043_lvs快速入门之TUN实践(原理详解)-.mp4 [22.8 MB]
  • 036_lvs快速入门之TUN实践(前置知识)-.mp4 [30.3 MB]
01项目管理基础7 集
  • 002_项目管理基础之项目环境(平台环境)-.mp4 [32.8 MB]
  • 004_项目管理基础之项目管理(管理方式)-.mp4 [26.7 MB]
  • 005_项目管理基础之项目管理(管理工具)-.mp4 [13.1 MB]
  • 001_项目管理基础之项目环境(项目基础)-.mp4 [42.7 MB]
  • 000_课程概况-.mp4 [6.7 MB]
  • 006_项目管理基础之项目管理(工具模式)-.mp4 [21.9 MB]
  • 003_项目管理基础之项目环境(项目环境)-.mp4 [14.5 MB]
06Ansible 进阶之变量进阶6 集
  • 049_ansible进阶之变量进阶(变量-主机属性)-.mp4 [29.7 MB]
  • 048_ansible进阶之变量进阶(变量基础)-.mp4 [24.0 MB]
  • 052_ansible进阶之变量进阶(变量-playbook)-.mp4 [21.1 MB]
  • 051_ansible进阶之变量进阶(变量-命令行)-.mp4 [27.7 MB]
  • 053_ansible进阶之变量进阶(变量-专用文件)-.mp4 [31.0 MB]
  • 050_ansible进阶之变量进阶(变量-主机列表)-.mp4 [41.3 MB]
04Ansible 快速入门之常用模块13 集
  • 033_快速入门之常用模块(系列命令1)-.mp4 [44.7 MB]
  • 035_快速入门之常用模块(系列命令3)-.mp4 [16.5 MB]
  • 034_快速入门之常用模块(系列命令2)-.mp4 [35.4 MB]
  • 022_快速入门之常用模块(日常模块1)-.mp4 [41.9 MB]
  • 025_快速入门之常用模块(系统模块2)-.mp4 [29.9 MB]
  • 029_快速入门之常用模块(文件模块2)-.mp4 [24.5 MB]
  • 027_快速入门之常用模块(系统模块4)-.mp4 [23.1 MB]
  • 030_快速入门之常用模块(文件模块3)-.mp4 [29.6 MB]
  • 028_快速入门之常用模块(文件模块1)-.mp4 [35.4 MB]
  • 032_快速入门之常用模块(应用模块2)-.mp4 [34.5 MB]
  • 024_快速入门之常用模块(系统模块1)-.mp4 [46.7 MB]
  • 023_快速入门之常用模块(日常模块2)-.mp4 [33.7 MB]
  • 026_快速入门之常用模块(系统模块3)-.mp4 [33.2 MB]
05Ansible 快速入门之playbook12 集
  • 037_快速入门之playbook(YAML详解)-.mp4 [50.8 MB]
  • 047_快速入门之playbook(标签2)-.mp4 [41.4 MB]
  • 041_快速入门之playbook(基础属性3)-.mp4 [35.5 MB]
  • 046_快速入门之playbook(标签1)-.mp4 [28.7 MB]
  • 044_快速入门之playbook(任务依赖1)-.mp4 [29.2 MB]
  • 045_快速入门之playbook(任务依赖2)-.mp4 [29.9 MB]
  • 039_快速入门之playbook(基础属性1)-.mp4 [55.3 MB]
  • 036_快速入门之playbook(基础)-.mp4 [23.6 MB]
  • 043_快速入门之playbook(异常中断)-.mp4 [46.6 MB]
  • 042_快速入门之playbook(基础属性4)-.mp4 [23.1 MB]
  • 038_第二天总结-.mp4 [28.6 MB]
  • 040_快速入门之playbook(基础属性2)-.mp4 [23.5 MB]
08Ansible 进阶之Role14 集
  • 079_第四天总结-.mp4 [24.8 MB]
  • 068_ansible进阶之Role(简单案例2)-.mp4 [47.9 MB]
  • 067_ansible进阶之Role(简单案例1)-.mp4 [29.0 MB]
  • 078_ansible进阶之Role(综合实践4)-.mp4 [36.9 MB]
  • 073_ansible进阶之Role(扩展功能2)-.mp4 [46.4 MB]
  • 072_ansible进阶之Role(扩展功能1)-.mp4 [22.1 MB]
  • 074_ansible进阶之Role(扩展功能3)-.mp4 [14.8 MB]
  • 076_ansible进阶之Role(综合实践2)-.mp4 [40.8 MB]
  • 077_ansible进阶之Role(综合实践3)-.mp4 [38.0 MB]
  • 066_ansible进阶之Role(角色基础)-.mp4 [28.1 MB]
  • 071_ansible进阶之Role(角色管理)-.mp4 [36.3 MB]
  • 075_ansible进阶之Role(综合实践)-.mp4 [20.6 MB]
  • 069_ansible进阶之Role(简单案例3)-.mp4 [17.2 MB]
  • 070_ansible进阶之Role(role结构)-.mp4 [16.3 MB]
07Ansible 进阶之模板12 集
  • 057_ansible进阶之模板(条件2)-.mp4 [27.5 MB]
  • 055_ansible进阶之模板(快速入门)-.mp4 [45.0 MB]
  • 065_ansible进阶之模板(for流程2)-.mp4 [34.0 MB]
  • 061_ansible进阶之模板(迭代进阶2)-.mp4 [37.9 MB]
  • 056_ansible进阶之模板(条件1)-.mp4 [44.3 MB]
  • 054_ansible进阶之模板(模板基础)-.mp4 [24.4 MB]
  • 064_ansible进阶之模板(for流程1)-.mp4 [19.1 MB]
  • 060_ansible进阶之模板(迭代进阶1)-.mp4 [21.8 MB]
  • 058_第三天总结-.mp4 [22.9 MB]
  • 063_ansible进阶之模板(if流程)-.mp4 [40.7 MB]
  • 059_ansible进阶之模板(迭代)-.mp4 [30.2 MB]
  • 062_ansible进阶之模板(流程基础1)-.mp4 [17.4 MB]
02Ansible 快速入门之基础知识1 集
  • 007_快速入门之基础知识(简介+功能简介)-.mp4 [29.8 MB]
03Ansible 快速入门之软件部署13 集
  • 015_快速入门之软件部署(原理详解)-.mp4 [29.7 MB]
  • 010_快速入门之软件部署(软件安装)-.mp4 [15.6 MB]
  • 016_快速入门之软件部署(配置详解)-.mp4 [45.6 MB]
  • 017_快速入门之软件部署(简单实践1)-.mp4 [32.5 MB]
  • 013_快速入门之软件部署(主机清单1)-.mp4 [42.5 MB]
  • 009_快速入门之软件部署(部署简介+准备工作2)-.mp4 [17.8 MB]
  • 020_快速入门之软件部署(主机进阶实践)-.mp4 [48.3 MB]
  • 012_快速入门之软件部署(简单使用2)-.mp4 [32.6 MB]
  • 021_快速入门之软件部署(命令执行过程)-.mp4 [30.7 MB]
  • 008_快速入门之软件部署(部署简介+准备工作1)-.mp4 [31.4 MB]
  • 014_快速入门之软件部署(主机清单2)-.mp4 [29.5 MB]
  • 018_快速入门之软件部署(简单实践2)-.mp4 [33.2 MB]
  • 011_快速入门之软件部署(简单使用1)-.mp4 [41.8 MB]
03gRPC接口类型1 集
  • 03_gRPC接口类型-.mp4 [6.5 MB]
02HTTP2协议2 集
  • 022_HTTP2协议介绍-.mp4 [21.5 MB]
  • 021_HTTP1协议的不足-.mp4 [10.6 MB]
04ProtocolBuffers3 集
  • 041_ProtocolBuffers简介及文档结构和注释语法-.mp4 [8.2 MB]
  • 042_数据类型与消息类型的语法-.mp4 [15.7 MB]
  • 043_接口服务定义语法-.mp4 [6.9 MB]
06服务器与客户端程序编写6 集
  • 066_双向流式RPC调用服务器与客户端实现-.mp4 [13.7 MB]
  • 061_服务器一元RPC调用方法实现-.mp4 [15.1 MB]
  • 063_客户端一元RPC调用实现-.mp4 [12.8 MB]
  • 064_服务器流式RPC调用服务器与客户端实现-.mp4 [13.7 MB]
  • 065_客户端流式RPC调用服务器与客户端实现-.mp4 [11.8 MB]
  • 062_服务器启动代码实现-.mp4 [12.8 MB]
01gRPC框架课程知识介绍及gRPC简介架构和使用方法1 集
  • 01_第四部分gRPC框架课程知识介绍及gRPC简介架构和使用方法-.mp4 [6.9 MB]
05案例接口定义与代码生成3 集
  • 052_案例接口定义2-.mp4 [7.4 MB]
  • 053_编译代码生成与生成文件说明-.mp4 [10.8 MB]
  • 051_案例接口定义1-.mp4 [13.0 MB]
09_评分卡21 集
  • 12_XGBoost的API练习_印第安糖尿病案例_.mp4 [37.3 MB]
  • 17_lightgbm跨时间交叉验证思路分析_.mp4 [37.3 MB]
  • 20_问题说明_.mp4 [18.1 MB]
  • 04_逻辑回归评分卡模型代码实现_.mp4 [33.0 MB]
  • 18_lightgbm跨时间交叉验证代码实现_.mp4 [55.9 MB]
  • 14_XGBoost常用调参_.mp4 [34.0 MB]
  • 11_XGBoost和GBDT区别说明_.mp4 [23.5 MB]
  • 19_lightgbm评分卡实现_.mp4 [10.6 MB]
  • 05_逻辑回归评分卡lgbm特征选择_.mp4 [40.5 MB]
  • 03_评分卡模型评价_ROC图的绘制_.mp4 [8.4 MB]
  • 21_内容回顾_.mp4 [77.5 MB]
  • 09_评分卡流程回顾_.mp4 [11.3 MB]
  • 06_逻辑回归评分卡模型评估报告_.mp4 [39.0 MB]
  • 08_逻辑回归评分卡计算信用分和评级_.mp4 [42.2 MB]
  • 16_lightgbm简介_.mp4 [26.1 MB]
  • 13_XGBoost的early_stopping参数_.mp4 [19.7 MB]
  • 15_集成学习总结_.mp4 [13.6 MB]
  • 01_内容回顾_.mp4 [45.6 MB]
  • 02_评分卡模型评价_KS值_.mp4 [69.8 MB]
  • 07_逻辑回归评分卡模型评估报告2_.mp4 [19.8 MB]
  • 10_GBDT原理简介_.mp4 [27.0 MB]
3_视频20 集
  • 19.癌症分类预测步骤分析_.mp4 [7.7 MB]
  • 18.逻辑回归api介绍_.mp4 [4.5 MB]
  • 12.正则化线性模型_.mp4 [15.5 MB]
  • 14.模型的保存和加载_.mp4 [11.3 MB]
  • 13.宀洖褰抇.mp4 [9.9 MB]
  • 5.线性回归的损失和优化_.mp4 [42.4 MB]
  • 23.浠婃棩鎬荤粨_.mp4 [12.5 MB]
  • 10.过拟合和欠拟合_.mp4 [17.4 MB]
  • 17.逻辑回归的损失以及优化_.mp4 [12.3 MB]
  • 16.逻辑回归的原理_.mp4 [24.1 MB]
  • 3.机器学习算法是如何学习的_.mp4 [20.9 MB]
  • 2.鏁板锛氭眰瀵糭.mp4 [27.7 MB]
  • 9.波士顿房价预测_.mp4 [23.7 MB]
  • 15.逻辑回归简介_.mp4 [6.5 MB]
  • 7.线性回归api再介绍_.mp4 [8.2 MB]
  • 21.分类评估方法_.mp4 [21.6 MB]
  • 20.癌症分类预测实现_.mp4 [27.7 MB]
  • 22.ROC鏇茬嚎鐨勭粯鍒禵.mp4 [23.9 MB]
  • 8.波士顿房价预测步骤分析_.mp4 [11.4 MB]
  • 6.姊害涓嬮檷娉昣.mp4 [27.4 MB]
finance26 条
  • ._finance_ebitdatointerest.h5 [4.0 KB]
  • ._finance_ebitda_ttm.h5 [4.0 KB]
  • ._finance_ebit_ttm2.h5 [4.0 KB]
  • finance_ebitps.h5 [941.9 KB]
  • finance_ebitdatosales.h5 [542.2 KB]
  • ._finance_ebitdatosales.h5 [4.0 KB]
  • finance_ebitdatodebt.h5 [541.3 KB]
  • finance_ebitdatointerest.h5 [492.9 KB]
  • finance_ebitdatointerestdebt.h5 [551.5 KB]
  • ._finance_ebit2.h5 [4.0 KB]
  • finance_ebit.h5 [924.6 KB]
  • finance_ebitda2_ttm.h5 [927.0 KB]
  • finance_ebitdaps.h5 [466.0 KB]
  • ._finance_ebitdatointerestdebt.h5 [4.0 KB]
  • ._finance_ebit2_ttm.h5 [4.0 KB]
  • finance_ebitda.h5 [532.7 KB]
  • finance_ebit_ttm2.h5 [933.7 KB]
  • ._finance_ebitdatodebt.h5 [4.0 KB]
  • ._finance_ebitdaps.h5 [4.0 KB]
  • finance_ebit2.h5 [858.3 KB]
  • ._finance_ebitda2_ttm.h5 [4.0 KB]
  • ._finance_ebit.h5 [4.0 KB]
  • ._finance_ebitda.h5 [4.0 KB]
  • ._finance_ebitps.h5 [4.0 KB]
  • finance_ebit2_ttm.h5 [937.3 KB]
  • finance_ebitda_ttm.h5 [915.6 KB]
day36 条
  • day_pb_lf.h5 [20.9 MB]
  • ._day_ev2_to_ebitda.h5 [4.0 KB]
  • ._day_eps_ttm.h5 [4.0 KB]
  • day_dividendyield2.h5 [40.9 MB]
  • day_pre_close.h5 [41.8 MB]
  • ._day_high.h5 [4.0 KB]
  • ._day_estpeg_FTM.h5 [4.0 KB]
  • ._day_ev2.h5 [4.0 KB]
  • day_low.h5 [40.9 MB]
  • day_ev2_to_ebitda.h5 [43.6 MB]
  • ._day_open.h5 [4.0 KB]
  • ._day_pb_lf.h5 [4.0 KB]
  • day_employee.h5 [2.0 MB]
  • day_estpeg_FTM.h5 [42.6 MB]
  • ._day_employee.h5 [4.0 KB]
  • ._day_close.h5 [4.0 KB]
  • day_close.h5 [41.6 MB]
  • ._day_ev1.h5 [4.0 KB]
  • ._day_amt.h5 [4.0 KB]
  • ._day_adjfactor.h5 [4.0 KB]
  • day_open.h5 [40.9 MB]
  • day_adjfactor.h5 [12.9 MB]
  • day_maxupordown.h5 [1.2 MB]
  • day_eps_ttm.h5 [15.2 MB]
  • day_estpb_FY1.h5 [40.9 MB]
  • day_ev.h5 [41.4 MB]
  • ._day_pre_close.h5 [4.0 KB]
  • day_high.h5 [41.1 MB]
  • day_ev2.h5 [43.0 MB]
  • ._day_ev.h5 [4.0 KB]
  • ._day_dividendyield2.h5 [4.0 KB]
  • ._day_estpb_FY1.h5 [4.0 KB]
  • day_ev1.h5 [43.0 MB]
  • ._day_low.h5 [4.0 KB]
  • day_amt.h5 [33.1 MB]
  • ._day_maxupordown.h5 [4.0 KB]
date2 条
  • transaction_date.csv [77.4 KB]
  • ._transaction_date.csv [4.0 KB]
list10 条
  • ._财务指标列表_financelist3.xlsx [4.0 KB]
  • ._日线字段列表.xlsx [4.0 KB]
  • 财务指标列表_financelist2.xlsx [13.4 KB]
  • ._stocklistA.h5 [4.0 KB]
  • 财务指标列表_financelist3.xlsx [6.1 KB]
  • ._财务指标列表_financelist2.xlsx [4.0 KB]
  • 日线字段列表.xlsx [7.0 KB]
  • stocklistA.h5 [1.5 MB]
  • 财务指标列表_financelist1.xlsx [8.9 KB]
  • ._财务指标列表_financelist1.xlsx [4.0 KB]
FBlocation4 条
  • test.csv [261.2 MB]
  • train.csv [1.2 GB]
  • ._test.csv [4.0 KB]
  • ._train.csv [4.0 KB]
.ipynb_checkpoints11 条
  • 3.pandas高级数据处理-checkpoint.ipynb [72.0 B]
  • dating.txt [25.5 KB]
  • ._dating.txt [4.0 KB]
  • directory.csv [3.9 MB]
  • IMDB-Movie-Data.csv [302.5 KB]
  • ._stock_day.csv [4.0 KB]
  • ._directory.csv [4.0 KB]
  • stock_day.csv [67.6 KB]
  • ._IMDB-Movie-Data.csv [4.0 KB]
  • ._Sarcasm_Headlines_Dataset.json [4.0 KB]
  • Sarcasm_Headlines_Dataset.json [5.4 MB]
.ipynb_checkpoints30 条
  • 用pandas实现标准化-checkpoint.ipynb [72.0 B]
  • 折线图绘制与显示-checkpoint.ipynb [72.0 B]
  • 案例：癌症分类预测-良／恶性乳腺癌肿瘤预测-checkpoint.ipynb [581.0 B]
  • ndarray运算-checkpoint.ipynb [17.5 KB]
  • 文本特征提取-checkpoint.ipynb [72.0 B]
  • 文件的读取和存储-checkpoint.ipynb [16.2 KB]
  • hello_jupyter-checkpoint.ipynb [72.0 B]
  • 基本数据操作-checkpoint.ipynb [142.2 KB]
  • 数据离散化-checkpoint.ipynb [22.2 KB]
  • 缺失值的处理-checkpoint.ipynb [72.0 B]
  • Pandas介绍-checkpoint.ipynb [72.0 B]
  • 显示温度变化状况-checkpoint.ipynb [72.0 B]
  • 预测facebook签到位置-checkpoint.ipynb [72.0 B]
  • ndarray介绍-checkpoint.ipynb [72.0 B]
  • 分组与聚合-checkpoint.ipynb [72.0 B]
  • 癌症分类预测-checkpoint.ipynb [72.0 B]
  • 波士顿房价预测-checkpoint.ipynb [72.0 B]
  • Untitled1-checkpoint.ipynb [72.0 B]
  • 数据的合并-checkpoint.ipynb [72.0 B]
  • scikit-learn中数据集介绍-checkpoint.ipynb [581.0 B]
  • 特征提取-checkpoint.ipynb [72.0 B]
  • 常见图形的绘制-checkpoint.ipynb [72.0 B]
  • 线性回归api初步使用-checkpoint.ipynb [72.0 B]
  • 案例-鸢尾花种类预测-checkpoint.ipynb [2.9 KB]
  • 肿瘤预测-checkpoint.ipynb [72.0 B]
  • ndarray的基本操作-checkpoint.ipynb [44.5 KB]
  • 岭回归-checkpoint.ipynb [2.2 KB]
  • K-近邻算法API演示-checkpoint.ipynb [581.0 B]
  • 特征工程：字典特征提取-checkpoint.ipynb [72.0 B]
  • 交叉表和透视表-checkpoint.ipynb [72.0 B]
inspectionProfiles37 条
  • profiles_settings.xml [228.0 B]
  • 4_源代码(1).iml [459.0 B]
  • modules.xml [274.0 B]
  • workspace.xml [27.6 KB]
  • misc.xml [212.0 B]
  • 用pandas实现标准化.ipynb [4.5 KB]
  • Snipaste_2019-06-08_10-44-27.png [457.1 KB]
  • ._Snipaste_2019-06-08_11-20-40.png [4.0 KB]
  • ._Snipaste_2019-06-08_10-16-07.png [4.0 KB]
  • ._Snipaste_2019-06-08_15-43-42.png [4.0 KB]
  • Snipaste_2019-06-08_09-51-25.png [479.7 KB]
  • Snipaste_2019-06-08_17-23-31.png [409.2 KB]
  • Snipaste_2019-06-08_10-24-55.png [644.4 KB]
  • ._Snipaste_2019-06-08_11-15-07.png [4.0 KB]
  • ._Snipaste_2019-06-08_10-54-01.png [4.0 KB]
  • Snipaste_2019-06-08_11-15-07.png [581.1 KB]
  • Snipaste_2019-06-08_16-10-17.png [494.1 KB]
  • ._Snipaste_2019-06-08_10-41-32.png [4.0 KB]
  • ._Snipaste_2019-06-08_17-23-31.png [4.0 KB]
  • ._Snipaste_2019-06-08_10-44-27.png [4.0 KB]
  • ._Snipaste_2019-06-08_10-24-55.png [4.0 KB]
  • ._Snipaste_2019-06-08_16-10-17.png [4.0 KB]
  • Snipaste_2019-06-08_11-08-10.png [614.7 KB]
  • 癌症分类预测.ipynb [4.1 KB]
  • Snipaste_2019-06-08_12-28-37.png [569.1 KB]
  • ._Snipaste_2019-06-08_12-28-37.png [4.0 KB]
  • ._Snipaste_2019-06-08_11-08-10.png [4.0 KB]
  • Snipaste_2019-06-08_17-06-38.png [403.5 KB]
  • test.pkl [669.0 B]
  • Snipaste_2019-06-08_11-20-40.png [562.5 KB]
  • ._Snipaste_2019-06-08_09-51-25.png [4.0 KB]
  • Snipaste_2019-06-08_10-54-01.png [580.4 KB]
  • Snipaste_2019-06-08_10-16-07.png [538.2 KB]
  • ._Snipaste_2019-06-08_17-06-38.png [4.0 KB]
  • Snipaste_2019-06-08_15-43-42.png [354.1 KB]
  • Snipaste_2019-06-08_10-41-32.png [513.6 KB]
  • 波士顿房价预测.ipynb [6.9 KB]
1_教学资料8 条
  • 课后作业.md [67.0 B]
  • 人工神经元.png [62.4 KB]
  • 激活函数.png [5.7 KB]
  • ._人工神经元.png [4.0 KB]
  • 机器学习算法.xmind [56.5 KB]
  • ._激活函数.png [4.0 KB]
  • ._机器学习算法.xmind [4.0 KB]
  • ._课后作业.md [4.0 KB]
3_视频17 集
  • 14.线性回归的公式_.mp4 [15.4 MB]
  • 16.线性回归api初步使用_.mp4 [14.6 MB]
  • 13.预测facebook签到位置案例实现_.mp4 [42.9 MB]
  • 3.kd树的构造方法_.mp4 [20.5 MB]
  • 10.鸢尾花种类预测实现_.mp4 [16.1 MB]
  • 10.交叉验证和网格搜索_1_.mp4 [25.9 MB]
  • 9.鸢尾花种类预测步骤分析_.mp4 [8.4 MB]
  • 11.KNN的优点和缺点_.mp4 [16.6 MB]
  • 17.一个问题：机器学习算法是如何学习的_.mp4 [4.2 MB]
  • 6.查看数据分布_.mp4 [17.5 MB]
  • 7.数据集划分_.mp4 [10.9 MB]
  • 12.预测facebook签到位置步骤分析_.mp4 [20.6 MB]
  • 15.线性回归的应用_.mp4 [20.2 MB]
  • 4.kd树查找最近点的方法_.mp4 [23.5 MB]
  • 18.浠婃棩鎬荤粨_.mp4 [16.2 MB]
  • 5.scikit-learn的数据集API介绍_.mp4 [21.8 MB]
  • 11.交叉验证和网格搜索的使用_.mp4 [16.8 MB]
1_教学资料1 条
  • ._Snipaste_2019-06-06_11-51-43.png [4.0 KB]
inspectionProfiles5 条
  • profiles_settings.xml [228.0 B]
  • 4_源代码.iml [459.0 B]
  • workspace.xml [27.6 KB]
  • misc.xml [212.0 B]
  • modules.xml [274.0 B]
.ipynb_checkpoints36 条
  • 数据的合并-checkpoint.ipynb [72.0 B]
  • 鸢尾花种类预测-checkpoint.ipynb [72.0 B]
  • Pandas介绍-checkpoint.ipynb [72.0 B]
  • K-近邻算法API演示-checkpoint.ipynb [581.0 B]
  • 查看数据分布与数据集划分-checkpoint.ipynb [72.0 B]
  • 去量纲化-checkpoint.ipynb [72.0 B]
  • ndarray介绍-checkpoint.ipynb [72.0 B]
  • ndarray运算-checkpoint.ipynb [17.5 KB]
  • hello_jupyter-checkpoint.ipynb [72.0 B]
  • 特征预处理-checkpoint.ipynb [72.0 B]
  • 获取数据集-checkpoint.ipynb [72.0 B]
  • 数据离散化-checkpoint.ipynb [22.2 KB]
  • ndarray的基本操作-checkpoint.ipynb [44.5 KB]
  • 线性回归api初步使用-checkpoint.ipynb [72.0 B]
  • 缺失值的处理-checkpoint.ipynb [72.0 B]
  • Untitled1-checkpoint.ipynb [72.0 B]
  • 波士顿房价预测-checkpoint.ipynb [72.0 B]
  • 常见图形的绘制-checkpoint.ipynb [72.0 B]
  • Untitled2-checkpoint.ipynb [72.0 B]
  • 文件的读取和存储-checkpoint.ipynb [16.2 KB]
  • 预测facebook签到位置-checkpoint.ipynb [72.0 B]
  • scikit-learn中数据集介绍-checkpoint.ipynb [581.0 B]
  • 交叉表和透视表-checkpoint.ipynb [72.0 B]
  • Untitled4-checkpoint.ipynb [72.0 B]
  • Untitled-checkpoint.ipynb [3.4 KB]
  • pandas案例-checkpoint.ipynb [72.0 B]
  • 折线图绘制与显示-checkpoint.ipynb [72.0 B]
  • Untitled3-checkpoint.ipynb [72.0 B]
  • sklearn数据集的获取-checkpoint.ipynb [72.0 B]
  • 分组与聚合-checkpoint.ipynb [72.0 B]
  • 显示温度变化状况-checkpoint.ipynb [72.0 B]
  • 案例-鸢尾花种类预测-checkpoint.ipynb [2.9 KB]
  • scikit-learn数据集API介绍-checkpoint.ipynb [3.4 KB]
  • 数据基本处理-checkpoint.ipynb [72.0 B]
  • 基本数据操作-checkpoint.ipynb [142.2 KB]
  • facebook签到位置预测-checkpoint.ipynb [72.0 B]
list1 条
  • ._财务指标列表_financelist1.xlsx [4.0 KB]
finance26 条
  • ._finance_ebitdatointerest.h5 [4.0 KB]
  • ._finance_ebit2.h5 [4.0 KB]
  • finance_ebitdatointerestdebt.h5 [551.5 KB]
  • ._finance_ebitps.h5 [4.0 KB]
  • ._finance_ebit2_ttm.h5 [4.0 KB]
  • finance_ebitda.h5 [532.7 KB]
  • finance_ebitdaps.h5 [466.0 KB]
  • ._finance_ebitdatodebt.h5 [4.0 KB]
  • ._finance_ebitda.h5 [4.0 KB]
  • finance_ebit2.h5 [858.3 KB]
  • finance_ebitda_ttm.h5 [915.6 KB]
  • finance_ebit2_ttm.h5 [937.3 KB]
  • ._finance_ebitda2_ttm.h5 [4.0 KB]
  • ._finance_ebitda_ttm.h5 [4.0 KB]
  • finance_ebitdatosales.h5 [542.2 KB]
  • ._finance_ebit.h5 [4.0 KB]
  • finance_ebit_ttm2.h5 [933.7 KB]
  • finance_ebitdatointerest.h5 [492.9 KB]
  • ._finance_ebit_ttm2.h5 [4.0 KB]
  • finance_ebitdatodebt.h5 [541.3 KB]
  • finance_ebitda2_ttm.h5 [927.0 KB]
  • ._finance_ebitdatointerestdebt.h5 [4.0 KB]
  • finance_ebitps.h5 [941.9 KB]
  • ._finance_ebitdaps.h5 [4.0 KB]
  • finance_ebit.h5 [924.6 KB]
  • ._finance_ebitdatosales.h5 [4.0 KB]
list6 条
  • 财务指标列表_financelist3.xlsx [6.1 KB]
  • stocklistA.h5 [1.5 MB]
  • 财务指标列表_financelist1.xlsx [8.9 KB]
  • 财务指标列表_financelist2.xlsx [13.4 KB]
  • ._日线字段列表.xlsx [4.0 KB]
  • 日线字段列表.xlsx [7.0 KB]
date2 条
  • ._transaction_date.csv [4.0 KB]
  • transaction_date.csv [77.4 KB]
list1 条
  • ._财务指标列表_financelist3.xlsx [4.0 KB]
list1 条
  • ._财务指标列表_financelist2.xlsx [4.0 KB]
day36 条
  • day_pre_close.h5 [41.8 MB]
  • ._day_ev.h5 [4.0 KB]
  • ._day_amt.h5 [4.0 KB]
  • day_estpeg_FTM.h5 [42.6 MB]
  • ._day_pb_lf.h5 [4.0 KB]
  • ._day_ev2.h5 [4.0 KB]
  • ._day_dividendyield2.h5 [4.0 KB]
  • ._day_ev2_to_ebitda.h5 [4.0 KB]
  • day_ev2_to_ebitda.h5 [43.6 MB]
  • ._day_ev1.h5 [4.0 KB]
  • day_close.h5 [41.6 MB]
  • day_adjfactor.h5 [12.9 MB]
  • day_amt.h5 [33.1 MB]
  • day_estpb_FY1.h5 [40.9 MB]
  • day_high.h5 [41.1 MB]
  • ._day_estpb_FY1.h5 [4.0 KB]
  • ._day_low.h5 [4.0 KB]
  • ._day_open.h5 [4.0 KB]
  • ._day_adjfactor.h5 [4.0 KB]
  • ._day_eps_ttm.h5 [4.0 KB]
  • ._day_close.h5 [4.0 KB]
  • day_employee.h5 [2.0 MB]
  • ._day_high.h5 [4.0 KB]
  • day_ev1.h5 [43.0 MB]
  • day_open.h5 [40.9 MB]
  • day_dividendyield2.h5 [40.9 MB]
  • ._day_maxupordown.h5 [4.0 KB]
  • day_ev2.h5 [43.0 MB]
  • ._day_estpeg_FTM.h5 [4.0 KB]
  • day_ev.h5 [41.4 MB]
  • day_low.h5 [40.9 MB]
  • day_maxupordown.h5 [1.2 MB]
  • ._day_pre_close.h5 [4.0 KB]
  • day_pb_lf.h5 [20.9 MB]
  • day_eps_ttm.h5 [15.2 MB]
  • ._day_employee.h5 [4.0 KB]
list1 条
  • ._stocklistA.h5 [4.0 KB]
FBlocation4 条
  • train.csv [1.2 GB]
  • ._test.csv [4.0 KB]
  • test.csv [261.2 MB]
  • ._train.csv [4.0 KB]
.ipynb_checkpoints18 条
  • 3.pandas高级数据处理-checkpoint.ipynb [72.0 B]
  • ._stock_day.csv [4.0 KB]
  • ._IMDB-Movie-Data.csv [4.0 KB]
  • directory.csv [3.9 MB]
  • IMDB-Movie-Data.csv [302.5 KB]
  • Sarcasm_Headlines_Dataset.json [5.4 MB]
  • ._Sarcasm_Headlines_Dataset.json [4.0 KB]
  • ._dating.txt [4.0 KB]
  • stock_day.csv [67.6 KB]
  • ._directory.csv [4.0 KB]
  • dating.txt [25.5 KB]
  • 去量纲化.ipynb [6.0 KB]
  • sklearn数据集的获取.ipynb [1.6 KB]
  • 鸢尾花种类预测.ipynb [7.8 KB]
  • 预测facebook签到位置.ipynb [9.4 KB]
  • 线性回归api初步使用.ipynb [2.3 KB]
  • pandas案例.ipynb [37.6 KB]
  • 查看数据分布与数据集划分.ipynb [54.5 KB]
1_教学资料29 条
  • Snipaste_2019-06-06_16-44-45.png [591.6 KB]
  • ._课后作业.md [4.0 KB]
  • ._Snipaste_2019-06-06_17-21-44.png [4.0 KB]
  • Snipaste_2019-06-06_12-05-51.png [339.4 KB]
  • ._Snipaste_2019-06-06_17-50-35.png [4.0 KB]
  • ._Snipaste_2019-06-06_15-27-16.png [4.0 KB]
  • Snipaste_2019-06-06_15-24-37.png [490.9 KB]
  • ._Snipaste_2019-06-06_10-52-01.png [4.0 KB]
  • Snipaste_2019-06-06_17-21-44.png [380.5 KB]
  • ._Snipaste_2019-06-06_16-01-49.png [4.0 KB]
  • Snipaste_2019-06-06_16-01-49.png [957.8 KB]
  • 机器学习算法.xmind [69.4 KB]
  • Snipaste_2019-06-06_16-50-49.png [516.6 KB]
  • 课后作业.md [125.0 B]
  • Snipaste_2019-06-06_17-50-35.png [313.1 KB]
  • Snipaste_2019-06-06_15-20-10.png [499.9 KB]
  • ._意见和建议.md [4.0 KB]
  • Snipaste_2019-06-06_17-11-28.png [483.6 KB]
  • ._Snipaste_2019-06-06_15-24-37.png [4.0 KB]
  • 意见和建议.md [113.0 B]
  • ._Snipaste_2019-06-06_16-44-45.png [4.0 KB]
  • Snipaste_2019-06-06_15-27-16.png [509.4 KB]
  • Snipaste_2019-06-06_11-51-43.png [487.2 KB]
  • ._Snipaste_2019-06-06_17-11-28.png [4.0 KB]
  • Snipaste_2019-06-06_10-52-01.png [601.8 KB]
  • ._Snipaste_2019-06-06_12-05-51.png [4.0 KB]
  • ._Snipaste_2019-06-06_15-20-10.png [4.0 KB]
  • ._机器学习算法.xmind [4.0 KB]
  • ._Snipaste_2019-06-06_16-50-49.png [4.0 KB]
3_视频13 集
  • 10.KNN的原理及实现步骤_.mp4 [23.8 MB]
  • 9.鍒嗙粍涓庤仛鍚坃2_.mp4 [21.4 MB]
  • 6.数据合并_1_.mp4 [11.1 MB]
  • 15.kd树的原理_.mp4 [20.2 MB]
  • 14.K值的选择对模型的影响_.mp4 [15.7 MB]
  • 8.交叉表与透视表_.mp4 [43.2 MB]
  • 3.缂哄け鍊煎鐞哶2_.mp4 [12.3 MB]
  • 9鍒嗙粍涓庤仛鍚坃1_.mp4 [6.9 MB]
  • 7.数据合并_2_.mp4 [31.5 MB]
  • 4.数据离散化_.mp4 [26.7 MB]
  • 2.缂哄け鍊煎鐞哶1_.mp4 [38.0 MB]
  • 11.k近邻算法api初步使用_.mp4 [17.4 MB]
  • 16.浠婃棩鎬荤粨_.mp4 [15.2 MB]
1_教学资料36 条
  • ._Snipaste_2019-06-04_11-03-01.png [4.0 KB]
  • ._Snipaste_2019-06-04_11-56-17.png [4.0 KB]
  • Snipaste_2019-06-04_17-16-28.png [569.9 KB]
  • ._Snipaste_2019-06-04_17-21-52.png [4.0 KB]
  • ._Snipaste_2019-06-04_11-59-57.png [4.0 KB]
  • Snipaste_2019-06-04_11-44-42.png [502.6 KB]
  • ._Snipaste_2019-06-04_12-26-05.png [4.0 KB]
  • Snipaste_2019-06-04_15-26-36.png [616.1 KB]
  • ._Snipaste_2019-06-04_10-04-34.png [4.0 KB]
  • Snipaste_2019-06-04_16-47-40.png [589.1 KB]
  • Snipaste_2019-06-04_16-32-32.png [404.2 KB]
  • ._Snipaste_2019-06-04_11-44-42.png [4.0 KB]
  • 机器学习算法.xmind [84.7 KB]
  • ._Snipaste_2019-06-04_16-47-40.png [4.0 KB]
  • ._机器学习算法.xmind [4.0 KB]
  • Snipaste_2019-06-04_11-56-17.png [410.4 KB]
  • ._Snipaste_2019-06-04_17-05-31.png [4.0 KB]
  • 意见和建议.md [178.0 B]
  • Snipaste_2019-06-04_15-32-59.png [766.0 KB]
  • ._Snipaste_2019-06-04_16-28-20.png [4.0 KB]
  • Snipaste_2019-06-04_11-59-57.png [401.6 KB]
  • ._科学计算库.xmind [4.0 KB]
  • ._Snipaste_2019-06-04_15-26-36.png [4.0 KB]
  • ._意见和建议.md [4.0 KB]
  • ._Snipaste_2019-06-04_15-32-59.png [4.0 KB]
  • Snipaste_2019-06-04_17-05-31.png [775.8 KB]
  • Snipaste_2019-06-04_17-21-52.png [519.9 KB]
  • Snipaste_2019-06-04_12-26-05.png [535.9 KB]
  • ._Snipaste_2019-06-04_16-50-11.png [4.0 KB]
  • Snipaste_2019-06-04_16-50-11.png [700.2 KB]
  • ._Snipaste_2019-06-04_16-32-32.png [4.0 KB]
  • 科学计算库.xmind [94.4 KB]
  • Snipaste_2019-06-04_11-03-01.png [529.6 KB]
  • Snipaste_2019-06-04_16-28-20.png [504.3 KB]
  • ._Snipaste_2019-06-04_17-16-28.png [4.0 KB]
  • Snipaste_2019-06-04_10-04-34.png [406.1 KB]
.ipynb_checkpoints1 条
  • 3.pandas高级数据处理-checkpoint.ipynb [72.0 B]
list10 条
  • ._财务指标列表_financelist2.xlsx [4.0 KB]
  • ._stocklistA.h5 [4.0 KB]
  • stocklistA.h5 [1.5 MB]
  • ._财务指标列表_financelist1.xlsx [4.0 KB]
  • 日线字段列表.xlsx [7.0 KB]
  • ._财务指标列表_financelist3.xlsx [4.0 KB]
  • ._日线字段列表.xlsx [4.0 KB]
  • 财务指标列表_financelist3.xlsx [6.1 KB]
  • 财务指标列表_financelist2.xlsx [13.4 KB]
  • 财务指标列表_financelist1.xlsx [8.9 KB]
day36 条
  • ._day_high.h5 [4.0 KB]
  • day_employee.h5 [2.0 MB]
  • ._day_close.h5 [4.0 KB]
  • ._day_amt.h5 [4.0 KB]
  • day_estpb_FY1.h5 [40.9 MB]
  • day_high.h5 [41.1 MB]
  • day_estpeg_FTM.h5 [42.6 MB]
  • day_adjfactor.h5 [12.9 MB]
  • ._day_ev.h5 [4.0 KB]
  • ._day_ev2.h5 [4.0 KB]
  • ._day_estpeg_FTM.h5 [4.0 KB]
  • day_ev2_to_ebitda.h5 [43.6 MB]
  • ._day_employee.h5 [4.0 KB]
  • day_low.h5 [40.9 MB]
  • ._day_adjfactor.h5 [4.0 KB]
  • day_ev.h5 [41.4 MB]
  • day_dividendyield2.h5 [40.9 MB]
  • day_open.h5 [40.9 MB]
  • ._day_low.h5 [4.0 KB]
  • ._day_dividendyield2.h5 [4.0 KB]
  • day_ev1.h5 [43.0 MB]
  • ._day_ev1.h5 [4.0 KB]
  • ._day_estpb_FY1.h5 [4.0 KB]
  • ._day_ev2_to_ebitda.h5 [4.0 KB]
  • ._day_eps_ttm.h5 [4.0 KB]
  • day_pb_lf.h5 [20.9 MB]
  • day_pre_close.h5 [41.8 MB]
  • ._day_pre_close.h5 [4.0 KB]
  • day_eps_ttm.h5 [15.2 MB]
  • day_ev2.h5 [43.0 MB]
  • day_amt.h5 [33.1 MB]
  • ._day_pb_lf.h5 [4.0 KB]
  • day_close.h5 [41.6 MB]
  • day_maxupordown.h5 [1.2 MB]
  • ._day_open.h5 [4.0 KB]
  • ._day_maxupordown.h5 [4.0 KB]
finance26 条
  • ._finance_ebitdatointerestdebt.h5 [4.0 KB]
  • ._finance_ebitdaps.h5 [4.0 KB]
  • finance_ebit2_ttm.h5 [937.3 KB]
  • finance_ebit2.h5 [858.3 KB]
  • ._finance_ebitdatointerest.h5 [4.0 KB]
  • finance_ebitdatodebt.h5 [541.3 KB]
  • ._finance_ebit_ttm2.h5 [4.0 KB]
  • ._finance_ebitda_ttm.h5 [4.0 KB]
  • finance_ebit_ttm2.h5 [933.7 KB]
  • finance_ebitda2_ttm.h5 [927.0 KB]
  • finance_ebitdaps.h5 [466.0 KB]
  • finance_ebitdatointerestdebt.h5 [551.5 KB]
  • ._finance_ebitdatosales.h5 [4.0 KB]
  • ._finance_ebitps.h5 [4.0 KB]
  • finance_ebitda_ttm.h5 [915.6 KB]
  • finance_ebitps.h5 [941.9 KB]
  • finance_ebit.h5 [924.6 KB]
  • finance_ebitdatointerest.h5 [492.9 KB]
  • ._finance_ebitda2_ttm.h5 [4.0 KB]
  • ._finance_ebitdatodebt.h5 [4.0 KB]
  • ._finance_ebit2.h5 [4.0 KB]
  • ._finance_ebit.h5 [4.0 KB]
  • ._finance_ebitda.h5 [4.0 KB]
  • finance_ebitda.h5 [532.7 KB]
  • finance_ebitdatosales.h5 [542.2 KB]
  • ._finance_ebit2_ttm.h5 [4.0 KB]
date12 条
  • ._transaction_date.csv [4.0 KB]
  • transaction_date.csv [77.4 KB]
  • ._stock_day.csv [4.0 KB]
  • ._IMDB-Movie-Data.csv [4.0 KB]
  • dating.txt [25.5 KB]
  • ._directory.csv [4.0 KB]
  • ._Sarcasm_Headlines_Dataset.json [4.0 KB]
  • Sarcasm_Headlines_Dataset.json [5.4 MB]
  • IMDB-Movie-Data.csv [302.5 KB]
  • ._dating.txt [4.0 KB]
  • directory.csv [3.9 MB]
  • stock_day.csv [67.6 KB]
.ipynb_checkpoints47 条
  • 特征预处理-checkpoint.ipynb [72.0 B]
  • k近邻API演示-checkpoint.ipynb [72.0 B]
  • scikit-learn中数据集介绍-checkpoint.ipynb [72.0 B]
  • 交叉表和透视表-checkpoint.ipynb [72.0 B]
  • K-近邻算法API演示-checkpoint.ipynb [581.0 B]
  • 显示温度变化状况-checkpoint.ipynb [72.0 B]
  • Untitled-checkpoint.ipynb [72.0 B]
  • 分组与聚合-checkpoint.ipynb [72.0 B]
  • 鸢尾花种类预测-checkpoint.ipynb [72.0 B]
  • 案例-鸢尾花种类预测-checkpoint.ipynb [2.9 KB]
  • 基本数据操作-checkpoint.ipynb [142.2 KB]
  • 文件的读取和存储-checkpoint.ipynb [16.2 KB]
  • pandas高级数据处理-checkpoint.ipynb [72.0 B]
  • 常见图形的绘制-checkpoint.ipynb [72.0 B]
  • ndarray的基本操作-checkpoint.ipynb [44.5 KB]
  • 数据离散化-checkpoint.ipynb [22.2 KB]
  • 数据集划分-checkpoint.ipynb [72.0 B]
  • 数据的合并-checkpoint.ipynb [72.0 B]
  • k近邻算法api初步使用-checkpoint.ipynb [72.0 B]
  • Pandas案例-checkpoint.ipynb [72.0 B]
  • ndarray运算-checkpoint.ipynb [17.5 KB]
  • 缺失值的处理-checkpoint.ipynb [72.0 B]
  • hello_jupyter-checkpoint.ipynb [72.0 B]
  • 查看数据分布-checkpoint.ipynb [72.0 B]
  • 文件读取与存储-checkpoint.ipynb [72.0 B]
  • scikit-learn数据集API介绍-checkpoint.ipynb [72.0 B]
  • ndarray介绍-checkpoint.ipynb [72.0 B]
  • pandas数据高级处理-checkpoint.ipynb [72.0 B]
  • Pandas介绍-checkpoint.ipynb [72.0 B]
  • 折线图绘制与显示-checkpoint.ipynb [72.0 B]
  • pandas数据高级处理.ipynb [148.6 KB]
  • k近邻算法api初步使用.ipynb [2.3 KB]
  • ._Snipaste_2019-06-07_12-08-39.png [4.0 KB]
  • ._Snipaste_2019-06-07_11-15-06.png [4.0 KB]
  • Snipaste_2019-06-07_12-08-39.png [488.0 KB]
  • Snipaste_2019-06-07_12-03-28.png [477.2 KB]
  • Snipaste_2019-06-07_11-53-22.png [534.5 KB]
  • Snipaste_2019-06-07_12-14-46.png [520.1 KB]
  • Snipaste_2019-06-07_10-04-05.png [578.9 KB]
  • Snipaste_2019-06-07_11-39-42.png [419.0 KB]
  • ._Snipaste_2019-06-07_10-04-05.png [4.0 KB]
  • Snipaste_2019-06-07_11-15-06.png [589.0 KB]
  • ._Snipaste_2019-06-07_12-14-46.png [4.0 KB]
  • ._Snipaste_2019-06-07_11-53-22.png [4.0 KB]
  • k近邻算法api初步使用.ipynb [2.0 KB]
  • ._Snipaste_2019-06-07_11-39-42.png [4.0 KB]
  • ._Snipaste_2019-06-07_12-03-28.png [4.0 KB]
.ipynb_checkpoints36 条
  • ndarray的计算-checkpoint.ipynb [72.0 B]
  • ndarray的属性-checkpoint.ipynb [995.0 B]
  • Numpy的基本操作-checkpoint.ipynb [581.0 B]
  • 绘图基本操作（辅助显示层）-checkpoint.ipynb [72.0 B]
  • 折线图绘制与显示-checkpoint.ipynb [72.0 B]
  • ndarray介绍-checkpoint.ipynb [72.0 B]
  • 形状修改-checkpoint.ipynb [72.0 B]
  • N维数组-ndarray-checkpoint.ipynb [72.0 B]
  • Numpy-checkpoint.ipynb [581.0 B]
  • ndarray的基本操作-checkpoint.ipynb [72.0 B]
  • ndarray的索引和切片-checkpoint.ipynb [72.0 B]
  • hello_jupyter-checkpoint.ipynb [72.0 B]
  • 类型修改和去重-checkpoint.ipynb [72.0 B]
  • ndarray的生成-checkpoint.ipynb [72.0 B]
  • 显示温度变化状况-checkpoint.ipynb [72.0 B]
  • hello_numpy-checkpoint.ipynb [72.0 B]
  • 常见图形绘制-checkpoint.ipynb [72.0 B]
  • hello_matplotlib-checkpoint.ipynb [72.0 B]
  • ndarray和list效率对比-checkpoint.ipynb [72.0 B]
  • Untitled-checkpoint.ipynb [72.0 B]
  • 逻辑运算-checkpoint.ipynb [72.0 B]
  • 常见图形的绘制-checkpoint.ipynb [72.0 B]
  • 折线图(plot)与基础绘图功能-checkpoint.ipynb [72.0 B]
  • 基础绘图功能-checkpoint.ipynb [34.1 KB]
  • 基本操作-checkpoint.ipynb [72.0 B]
  • ndarray运算-checkpoint.ipynb [17.5 KB]
  • test_1.png [1.2 KB]
  • 基础绘图功能.ipynb [229.1 KB]
  • test.png [28.3 KB]
  • 常见图形的绘制.ipynb [30.3 KB]
  • ._test.png [4.0 KB]
  • 基本操作.ipynb [21.0 KB]
  • hello_numpy.ipynb [2.8 KB]
  • N维数组-ndarray.ipynb [2.7 KB]
  • ._test_1.png [4.0 KB]
  • hello_matplotlib.ipynb [44.8 KB]
2_其它资料2 条
  • 意见和建议.md [345.0 B]
  • ._意见和建议.md [4.0 KB]
3_视频15 集
  • 16.均匀分布数组生成_.mp4 [13.1 MB]
  • 15.生成固定范围的数组_.mp4 [11.7 MB]
  • 2.Matplotlib三层结构_.mp4 [20.8 MB]
  • 3.画图的三个步骤_.mp4 [11.4 MB]
  • 4.淇濆瓨鍥惧儚_.mp4 [13.3 MB]
  • 21.浠婃棩鎬荤粨_.mp4 [14.0 MB]
  • 8.绘制函数图像_.mp4 [10.7 MB]
  • 7.多个坐标系绘图_.mp4 [20.8 MB]
  • 9.常见图形的意义_.mp4 [27.7 MB]
  • 19.均匀分布和正态分布的直方图_.mp4 [10.2 MB]
  • 5.完善原始折线图_1_.mp4 [29.4 MB]
  • 6.同一坐标系绘制多根曲线_.mp4 [18.2 MB]
  • 18.正态分布数组生成_.mp4 [9.9 MB]
  • 20.ndarray鐨勫熀鏈搷浣淿.mp4 [43.2 MB]
  • 10.常见图形的绘制_.mp4 [15.2 MB]
1_教学资料1 条
  • ._Snipaste_2019-06-01_11-58-07.png [4.0 KB]
1_教学资料17 条
  • Snipaste_2019-06-01_16-34-04.png [549.3 KB]
  • 科学计算库.xmind [100.4 KB]
  • ._Snipaste_2019-06-01_16-22-34.png [4.0 KB]
  • ._Snipaste_2019-06-01_16-34-04.png [4.0 KB]
  • ._simhei.ttf [4.0 KB]
  • ._Snipaste_2019-06-01_16-42-14.png [4.0 KB]
  • Snipaste_2019-06-01_16-22-34.png [385.8 KB]
  • ._课后作业.md [4.0 KB]
  • ._科学计算库.xmind [4.0 KB]
  • ._Snipaste_2019-06-01_15-21-32.png [4.0 KB]
  • Snipaste_2019-06-01_15-13-28.png [687.9 KB]
  • 课后作业.md [79.0 B]
  • Snipaste_2019-06-01_15-21-32.png [324.2 KB]
  • Snipaste_2019-06-01_11-58-07.png [336.8 KB]
  • Snipaste_2019-06-01_16-42-14.png [450.9 KB]
  • simhei.ttf [9.6 MB]
  • ._Snipaste_2019-06-01_15-13-28.png [4.0 KB]
.ipynb_checkpoints1 条
  • 3.k-means案例-checkpoint.ipynb [72.0 B]
instacart10 条
  • aisles.csv [2.5 KB]
  • ._orders.csv [4.0 KB]
  • ._products.csv [4.0 KB]
  • order_products__prior.csv [550.8 MB]
  • ._order_products__prior.csv [4.0 KB]
  • orders.csv [103.9 MB]
  • products.csv [2.1 MB]
  • ._aisles.csv [4.0 KB]
  • ._factor_returns.csv [4.0 KB]
  • factor_returns.csv [309.0 KB]
inspectionProfiles5 条
  • profiles_settings.xml [228.0 B]
  • misc.xml [212.0 B]
  • 4_源代码.iml [459.0 B]
  • workspace.xml [27.6 KB]
  • modules.xml [274.0 B]
.ipynb_checkpoints39 条
  • hello_jupyter-checkpoint.ipynb [72.0 B]
  • ndarray运算-checkpoint.ipynb [17.5 KB]
  • 案例-鸢尾花种类预测-checkpoint.ipynb [2.9 KB]
  • Pandas介绍-checkpoint.ipynb [72.0 B]
  • 预测facebook签到位置-checkpoint.ipynb [581.0 B]
  • 交叉表和透视表-checkpoint.ipynb [72.0 B]
  • 特征选择-checkpoint.ipynb [72.0 B]
  • 案例：癌症分类预测-良／恶性乳腺癌肿瘤预测-checkpoint.ipynb [581.0 B]
  • ndarray的基本操作-checkpoint.ipynb [44.5 KB]
  • 显示温度变化状况-checkpoint.ipynb [72.0 B]
  • 探究用户对物品类别的喜好细分降维-checkpoint.ipynb [72.0 B]
  • K-means聚类-checkpoint.ipynb [171.4 KB]
  • 聚类算法-checkpoint.ipynb [72.0 B]
  • 特征工程-特征提取-checkpoint.ipynb [1.6 KB]
  • 泰坦尼克号乘客生存预测-checkpoint.ipynb [72.0 B]
  • 折线图绘制与显示-checkpoint.ipynb [72.0 B]
  • 数据的合并-checkpoint.ipynb [72.0 B]
  • ndarray介绍-checkpoint.ipynb [72.0 B]
  • 分组与聚合-checkpoint.ipynb [72.0 B]
  • 案例：泰坦尼克号乘客生存预测-checkpoint.ipynb [72.0 B]
  • 文件的读取和存储-checkpoint.ipynb [16.2 KB]
  • 案例：探究用户对物品类别的喜好-checkpoint.ipynb [72.0 B]
  • K-近邻算法API演示-checkpoint.ipynb [581.0 B]
  • tf-idf-checkpoint.ipynb [72.0 B]
  • Untitled1-checkpoint.ipynb [72.0 B]
  • 常见图形的绘制-checkpoint.ipynb [72.0 B]
  • 缺失值的处理-checkpoint.ipynb [72.0 B]
  • 特征提取-checkpoint.ipynb [72.0 B]
  • 数据离散化-checkpoint.ipynb [22.2 KB]
  • scikit-learn中数据集介绍-checkpoint.ipynb [581.0 B]
  • 基本数据操作-checkpoint.ipynb [142.2 KB]
  • 癌症分类预测-checkpoint.ipynb [72.0 B]
  • 使用matplotlib绘制sigmoid激活函数的图形-checkpoint.ipynb [22.8 KB]
  • ._tree.dot [4.0 KB]
  • 泰坦尼克号乘客生存预测.ipynb [4.7 KB]
  • 癌症分类预测.ipynb [26.6 KB]
  • tree.dot [3.3 KB]
  • 使用matplotlib绘制sigmoid激活函数的图形.ipynb [22.8 KB]
  • 特征提取.ipynb [6.2 KB]
3_视频16 集
  • 11.字典特征提取_.mp4 [18.5 MB]
  • 20.浠婃棩鎬荤粨_.mp4 [10.9 MB]
  • 5.淇℃伅澧炵泭_.mp4 [31.1 MB]
  • 3.决策树算法简介_.mp4 [22.9 MB]
  • 6.淇℃伅澧炵泭鐜嘷.mp4 [13.0 MB]
  • 17.集成学习算法简介_.mp4 [9.5 MB]
  • 13.泰坦尼克号乘客生存预测步骤分析_.mp4 [17.2 MB]
  • 9.常见决策树类型_.mp4 [8.1 MB]
  • 18.Bagging集成学习的原理_.mp4 [18.3 MB]
  • 8.决策树构建的步骤_.mp4 [6.6 MB]
  • 7.基尼值和基尼指数_.mp4 [39.9 MB]
  • 12.文本特征提取_.mp4 [46.0 MB]
  • 14.泰坦尼克号乘客生存预测实现_.mp4 [23.6 MB]
  • 16.决策树的优缺点_.mp4 [3.4 MB]
  • 15.决策树可视化_.mp4 [12.4 MB]
  • 2.AUC鎸囨爣鐨勮绠梍.mp4 [7.7 MB]
data2 条
  • test_V2.csv [107.9 MB]
  • train_V2.csv [629.0 MB]
.ipynb_checkpoints5 条
  • Untitled-checkpoint(1).ipynb [72.0 B]
  • ._《绝地求生》玩家排名预测.docx [4.0 KB]
  • ._pubg.md [4.0 KB]
  • pubg.md [3.4 KB]
  • 《绝地求生》玩家排名预测.docx [16.5 MB]
img6 条
  • ._img3.png [4.0 KB]
  • img3.png [42.9 KB]
  • ._img2.png [4.0 KB]
  • ._img1.png [4.0 KB]
  • img2.png [721.1 KB]
  • img1.png [376.5 KB]
data2 条
  • train_V2.csv [629.0 MB]
  • test_V2.csv [107.9 MB]
.ipynb_checkpoints34 条
  • PUBG-checkpoint.ipynb [332.4 KB]
  • PUBG.ipynb [336.0 KB]
  • 《绝地求生》玩家排名预测.docx [16.5 MB]
  • ._《绝地求生》玩家排名预测.docx [4.0 KB]
  • 意见和建议.md [270.0 B]
  • ._机器学习算法.xmind [4.0 KB]
  • 机器学习算法.xmind [57.0 KB]
  • ._Snipaste_2019-06-09_11-09-27.png [4.0 KB]
  • Snipaste_2019-06-09_15-39-18.png [479.2 KB]
  • Snipaste_2019-06-09_17-07-30.png [374.4 KB]
  • Snipaste_2019-06-09_11-47-53.png [497.2 KB]
  • 课后作业.md [67.0 B]
  • ._Snipaste_2019-06-09_17-07-30.png [4.0 KB]
  • Snipaste_2019-06-09_11-01-19.png [447.3 KB]
  • Snipaste_2019-06-09_10-46-31.png [788.2 KB]
  • ._Snipaste_2019-06-09_10-05-52.png [4.0 KB]
  • ._Snipaste_2019-06-09_11-47-53.png [4.0 KB]
  • ._Snipaste_2019-06-09_17-09-02.png [4.0 KB]
  • ._课后作业.md [4.0 KB]
  • Snipaste_2019-06-09_17-09-02.png [306.3 KB]
  • Snipaste_2019-06-09_11-09-27.png [557.1 KB]
  • Snipaste_2019-06-09_15-19-59.png [415.0 KB]
  • ._Snipaste_2019-06-09_17-05-03.png [4.0 KB]
  • Snipaste_2019-06-09_10-10-43.png [272.0 KB]
  • ._Snipaste_2019-06-09_15-39-18.png [4.0 KB]
  • ._意见和建议.md [4.0 KB]
  • ._Snipaste_2019-06-09_10-46-31.png [4.0 KB]
  • Snipaste_2019-06-09_17-05-03.png [370.2 KB]
  • ._Snipaste_2019-06-09_15-19-59.png [4.0 KB]
  • Snipaste_2019-06-09_10-05-52.png [409.8 KB]
  • Snipaste_2019-06-09_12-21-12.png [463.5 KB]
  • ._Snipaste_2019-06-09_11-01-19.png [4.0 KB]
  • ._Snipaste_2019-06-09_12-21-12.png [4.0 KB]
  • ._Snipaste_2019-06-09_10-10-43.png [4.0 KB]
3_视频11 集
  • 9.绠楁硶浼樺寲_.mp4 [29.0 MB]
  • 8.聚类的模型评估_.mp4 [35.6 MB]
  • 2.boosting集成原理_.mp4 [31.1 MB]
  • 12.探究用户对物品类别的喜好_.mp4 [43.9 MB]
  • 3.bagging鍜宐oosting鐨勫尯鍒玙.mp4 [8.1 MB]
  • 13.算法选择指导_.mp4 [8.8 MB]
  • 5.聚类算法简介_.mp4 [10.2 MB]
  • 7.聚类算法实现流程（原理）_.mp4 [17.5 MB]
  • 6.聚类算法api初步使用_.mp4 [21.0 MB]
  • 10.鐗瑰緛閫夋嫨_.mp4 [51.9 MB]
  • 14.浠婃棩鎬荤粨_.mp4 [8.4 MB]
inspectionProfiles5 条
  • profiles_settings.xml [228.0 B]
  • 4_源代码.iml [459.0 B]
  • modules.xml [274.0 B]
  • workspace.xml [27.6 KB]
  • misc.xml [212.0 B]
.ipynb_checkpoints35 条
  • 案例：癌症分类预测-良／恶性乳腺癌肿瘤预测-checkpoint.ipynb [581.0 B]
  • scikit-learn中数据集介绍-checkpoint.ipynb [581.0 B]
  • 交叉表和透视表-checkpoint.ipynb [72.0 B]
  • K-近邻算法API演示-checkpoint.ipynb [581.0 B]
  • Untitled1-checkpoint.ipynb [72.0 B]
  • 特征工程-特征提取-checkpoint.ipynb [1.6 KB]
  • 特征提取-checkpoint.ipynb [72.0 B]
  • 聚类算法-checkpoint.ipynb [72.0 B]
  • ndarray运算-checkpoint.ipynb [17.5 KB]
  • Pandas介绍-checkpoint.ipynb [72.0 B]
  • 泰坦尼克号乘客生存预测-checkpoint.ipynb [72.0 B]
  • 探究用户对物品类别的喜好细分降维-checkpoint.ipynb [72.0 B]
  • 案例：探究用户对物品类别的喜好-checkpoint.ipynb [72.0 B]
  • 文件的读取和存储-checkpoint.ipynb [16.2 KB]
  • 基本数据操作-checkpoint.ipynb [142.2 KB]
  • ndarray介绍-checkpoint.ipynb [72.0 B]
  • 分组与聚合-checkpoint.ipynb [72.0 B]
  • 缺失值的处理-checkpoint.ipynb [72.0 B]
  • 癌症分类预测-checkpoint.ipynb [72.0 B]
  • 常见图形的绘制-checkpoint.ipynb [72.0 B]
  • 聚类算法api初步使用-checkpoint.ipynb [72.0 B]
  • 特征选择-checkpoint.ipynb [72.0 B]
  • 预测facebook签到位置-checkpoint.ipynb [581.0 B]
  • 案例-鸢尾花种类预测-checkpoint.ipynb [2.9 KB]
  • 案例：泰坦尼克号乘客生存预测-checkpoint.ipynb [72.0 B]
  • hello_jupyter-checkpoint.ipynb [72.0 B]
  • 特征降维-checkpoint.ipynb [72.0 B]
  • 探究用户对物品类别的喜好-checkpoint.ipynb [72.0 B]
  • 显示温度变化状况-checkpoint.ipynb [72.0 B]
  • 折线图绘制与显示-checkpoint.ipynb [72.0 B]
  • ndarray的基本操作-checkpoint.ipynb [44.5 KB]
  • 数据离散化-checkpoint.ipynb [22.2 KB]
  • K-means聚类-checkpoint.ipynb [171.4 KB]
  • 数据的合并-checkpoint.ipynb [72.0 B]
  • tf-idf-checkpoint.ipynb [72.0 B]
instacart8 条
  • ._orders.csv [4.0 KB]
  • ._aisles.csv [4.0 KB]
  • ._products.csv [4.0 KB]
  • aisles.csv [2.5 KB]
  • products.csv [2.1 MB]
  • ._order_products__prior.csv [4.0 KB]
  • order_products__prior.csv [550.8 MB]
  • orders.csv [103.9 MB]
.ipynb_checkpoints6 条
  • 3.k-means案例-checkpoint.ipynb [72.0 B]
  • factor_returns.csv [309.0 KB]
  • ._factor_returns.csv [4.0 KB]
  • 聚类算法api初步使用.ipynb [174.6 KB]
  • 特征降维.ipynb [4.5 KB]
  • 探究用户对物品类别的喜好.ipynb [9.1 KB]
1_教学资料38 条
  • ._Snipaste_2019-06-10_10-12-29.png [4.0 KB]
  • ._Snipaste_2019-06-10_10-45-51.png [4.0 KB]
  • ._Snipaste_2019-06-10_17-22-37.png [4.0 KB]
  • Snipaste_2019-06-10_16-06-57.png [793.7 KB]
  • Snipaste_2019-06-10_15-42-40.png [750.4 KB]
  • ._Snipaste_2019-06-10_10-06-15.png [4.0 KB]
  • Snipaste_2019-06-10_09-41-36.png [164.4 KB]
  • Snipaste_2019-06-10_15-30-39.png [366.3 KB]
  • ._Snipaste_2019-06-10_16-50-19.png [4.0 KB]
  • Snipaste_2019-06-10_11-52-34.png [385.9 KB]
  • Snipaste_2019-06-10_16-10-41.png [994.5 KB]
  • 意见和建议.md [228.0 B]
  • Snipaste_2019-06-10_17-27-54.png [340.8 KB]
  • Snipaste_2019-06-10_10-57-15.png [498.5 KB]
  • ._Snipaste_2019-06-10_09-48-41.png [4.0 KB]
  • ._Snipaste_2019-06-10_11-52-34.png [4.0 KB]
  • Snipaste_2019-06-10_12-03-25.png [728.7 KB]
  • ._Snipaste_2019-06-10_15-42-40.png [4.0 KB]
  • Snipaste_2019-06-10_10-50-11.png [523.5 KB]
  • ._Snipaste_2019-06-10_09-41-36.png [4.0 KB]
  • ._Snipaste_2019-06-10_16-10-41.png [4.0 KB]
  • Snipaste_2019-06-10_10-12-29.png [615.1 KB]
  • Snipaste_2019-06-10_17-22-37.png [858.5 KB]
  • ._Snipaste_2019-06-10_16-36-27.png [4.0 KB]
  • 机器学习算法.xmind [91.4 KB]
  • ._Snipaste_2019-06-10_12-03-25.png [4.0 KB]
  • ._意见和建议.md [4.0 KB]
  • ._机器学习算法.xmind [4.0 KB]
  • Snipaste_2019-06-10_16-36-27.png [853.7 KB]
  • ._Snipaste_2019-06-10_10-57-15.png [4.0 KB]
  • Snipaste_2019-06-10_16-50-19.png [427.2 KB]
  • Snipaste_2019-06-10_09-48-41.png [382.8 KB]
  • ._Snipaste_2019-06-10_10-50-11.png [4.0 KB]
  • ._Snipaste_2019-06-10_15-30-39.png [4.0 KB]
  • ._Snipaste_2019-06-10_17-27-54.png [4.0 KB]
  • Snipaste_2019-06-10_10-06-15.png [460.4 KB]
  • Snipaste_2019-06-10_10-45-51.png [345.2 KB]
  • ._Snipaste_2019-06-10_16-06-57.png [4.0 KB]
3_视频18 集
  • 11.监督学习和无监督学习_.mp4 [17.1 MB]
  • 2.人工智能概述_.mp4 [71.7 MB]
  • 13.分类模型的评估_.mp4 [26.1 MB]
  • 17.深度学习简介_.mp4 [21.2 MB]
  • 9.机器学习的几个基本概念_.mp4 [31.3 MB]
  • 7.机器学习工作流程_1_.mp4 [3.4 MB]
  • 5.人工智能的三要素_.mp4 [22.9 MB]
  • 6.什么是机器学习_.mp4 [10.5 MB]
  • 4.人工智能的主要分支_.mp4 [35.8 MB]
  • 16.Azure机器学习模型搭建实验_.mp4 [39.5 MB]
  • 3.人工智能发展历程_.mp4 [22.1 MB]
  • 18.Jupyter notebook的使用_.mp4 [39.7 MB]
  • 8.机器学习工作流程_2_.mp4 [10.8 MB]
  • 10.数据基本处理和特征工程_.mp4 [26.9 MB]
  • 19.浠婃棩鎬荤粨_.mp4 [13.5 MB]
  • 1.课程介绍_.mp4 [9.1 MB]
  • 12.半监督学习和强化学习_.mp4 [25.8 MB]
  • 14.回归模型的评估_.mp4 [25.5 MB]
.ipynb_checkpoints4 条
  • hello_matplotlib-checkpoint.ipynb [72.0 B]
  • hello_jupyter-checkpoint.ipynb [1.1 KB]
  • 绘图的基本步骤-checkpoint.ipynb [72.0 B]
  • hello_jupyter.ipynb [1.6 KB]
.ipynb_checkpoints23 条
  • Untitled-checkpoint.ipynb [72.0 B]
  • ._Azure机器学习模型搭建实验.doc [4.0 KB]
  • Azure机器学习模型搭建实验.doc [1.7 MB]
  • ._adult.data.csv [4.0 KB]
  • adult.data.csv [3.7 MB]
  • ._Snipaste_2019-05-31_15-42-55.png [4.0 KB]
  • ._科学计算库.xmind [4.0 KB]
  • Snipaste_2019-05-31_12-15-49.png [880.3 KB]
  • ._Snipaste_2019-05-31_15-47-13.png [4.0 KB]
  • ._Snipaste_2019-05-31_11-57-05.png [4.0 KB]
  • Snipaste_2019-05-31_11-57-05.png [1.0 MB]
  • ._Snipaste_2019-05-31_12-07-10.png [4.0 KB]
  • Snipaste_2019-05-31_11-54-56.png [1.4 MB]
  • ._课后作业.md [4.0 KB]
  • Snipaste_2019-05-31_15-47-13.png [582.4 KB]
  • 混淆矩阵.png [127.6 KB]
  • ._Snipaste_2019-05-31_11-54-56.png [4.0 KB]
  • Snipaste_2019-05-31_12-07-10.png [458.9 KB]
  • ._Snipaste_2019-05-31_12-15-49.png [4.0 KB]
  • Snipaste_2019-05-31_15-42-55.png [671.3 KB]
  • ._混淆矩阵.png [4.0 KB]
  • 课后作业.md [146.0 B]
  • 科学计算库.xmind [104.5 KB]
.ipynb_checkpoints2 条
  • hello_jupyter-checkpoint.ipynb [606.0 B]
  • hello_world-checkpoint.ipynb [1.3 KB]
3_视频13 集
  • 12.索引操作和赋值操作_.mp4 [27.8 MB]
  • 16.累计统计函数_.mp4 [21.1 MB]
  • 19.文件读取和存储_.mp4 [52.3 MB]
  • 5.矩阵乘法的性质_.mp4 [18.3 MB]
  • 15.缁熻杩愮畻_.mp4 [17.4 MB]
  • 14.閫昏緫杩愮畻_.mp4 [30.2 MB]
  • 3.缁熻杩愮畻_.mp4 [20.5 MB]
  • 2.閫昏緫杩愮畻_.mp4 [29.7 MB]
  • 17.鑷畾涔夎繍绠梍.mp4 [9.8 MB]
  • 20.浠婃棩鎬荤粨_.mp4 [19.2 MB]
  • 13.鎺掑簭鎿嶄綔_.mp4 [12.6 MB]
  • 10.DataFrame鐨勭储寮曡缃甠.mp4 [17.6 MB]
  • 6.数组与数组的运算_.mp4 [40.9 MB]
2_其它资料2 条
  • 周志华-机器学习_.pdf [85.7 MB]
  • ._周志华-机器学习_.pdf [4.0 KB]
1_教学资料14 条
  • ._Snipaste_2019-06-03_17-00-40.png [4.0 KB]
  • 科学计算库.xmind [115.0 KB]
  • ._Snipaste_2019-06-03_11-00-16.png [4.0 KB]
  • ._Snipaste_2019-06-03_10-36-00.png [4.0 KB]
  • 课后作业.md [4.0 B]
  • Snipaste_2019-06-03_11-00-16.png [445.8 KB]
  • Snipaste_2019-06-03_16-36-38.png [400.4 KB]
  • ._意见和建议.md [4.0 KB]
  • 意见和建议.md [167.0 B]
  • Snipaste_2019-06-03_17-00-40.png [342.3 KB]
  • Snipaste_2019-06-03_10-36-00.png [460.6 KB]
  • ._课后作业.md [4.0 KB]
  • ._科学计算库.xmind [4.0 KB]
  • ._Snipaste_2019-06-03_16-36-38.png [4.0 KB]
.ipynb_checkpoints1 条
  • 3.pandas高级数据处理-checkpoint.ipynb [72.0 B]
list10 条
  • stocklistA.h5 [1.5 MB]
  • 日线字段列表.xlsx [7.0 KB]
  • ._stocklistA.h5 [4.0 KB]
  • ._日线字段列表.xlsx [4.0 KB]
  • 财务指标列表_financelist3.xlsx [6.1 KB]
  • ._财务指标列表_financelist2.xlsx [4.0 KB]
  • ._财务指标列表_financelist3.xlsx [4.0 KB]
  • 财务指标列表_financelist1.xlsx [8.9 KB]
  • ._财务指标列表_financelist1.xlsx [4.0 KB]
  • 财务指标列表_financelist2.xlsx [13.4 KB]
date2 条
  • transaction_date.csv [77.4 KB]
  • ._transaction_date.csv [4.0 KB]
finance26 条
  • finance_ebit2_ttm.h5 [937.3 KB]
  • finance_ebitda.h5 [532.7 KB]
  • finance_ebit.h5 [924.6 KB]
  • finance_ebitps.h5 [941.9 KB]
  • ._finance_ebit2_ttm.h5 [4.0 KB]
  • finance_ebitdatodebt.h5 [541.3 KB]
  • finance_ebit_ttm2.h5 [933.7 KB]
  • ._finance_ebitda_ttm.h5 [4.0 KB]
  • finance_ebitdatointerest.h5 [492.9 KB]
  • ._finance_ebitdatointerestdebt.h5 [4.0 KB]
  • ._finance_ebit_ttm2.h5 [4.0 KB]
  • ._finance_ebitdatointerest.h5 [4.0 KB]
  • finance_ebitdatointerestdebt.h5 [551.5 KB]
  • finance_ebit2.h5 [858.3 KB]
  • ._finance_ebitdatodebt.h5 [4.0 KB]
  • ._finance_ebitdatosales.h5 [4.0 KB]
  • finance_ebitdaps.h5 [466.0 KB]
  • finance_ebitdatosales.h5 [542.2 KB]
  • finance_ebitda_ttm.h5 [915.6 KB]
  • ._finance_ebitdaps.h5 [4.0 KB]
  • ._finance_ebit.h5 [4.0 KB]
  • ._finance_ebit2.h5 [4.0 KB]
  • ._finance_ebitda.h5 [4.0 KB]
  • finance_ebitda2_ttm.h5 [927.0 KB]
  • ._finance_ebitda2_ttm.h5 [4.0 KB]
  • ._finance_ebitps.h5 [4.0 KB]
day44 条
  • ._day_dividendyield2.h5 [4.0 KB]
  • day_open.h5 [40.9 MB]
  • ._day_ev2.h5 [4.0 KB]
  • day_estpeg_FTM.h5 [42.6 MB]
  • ._day_eps_ttm.h5 [4.0 KB]
  • day_estpb_FY1.h5 [40.9 MB]
  • day_ev2_to_ebitda.h5 [43.6 MB]
  • day_high.h5 [41.1 MB]
  • day_eps_ttm.h5 [15.2 MB]
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  • directory.csv [3.9 MB]
  • ._stock_day.csv [4.0 KB]
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  • ._directory.csv [4.0 KB]
  • ._Sarcasm_Headlines_Dataset.json [4.0 KB]
  • Sarcasm_Headlines_Dataset.json [5.4 MB]
  • IMDB-Movie-Data.csv [302.5 KB]
  • ._IMDB-Movie-Data.csv [4.0 KB]
.ipynb_checkpoints45 条
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  • 数据合并-checkpoint.ipynb [72.0 B]
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  • pandas的文件读取和存储-checkpoint.ipynb [72.0 B]
  • 缺失值的处理-checkpoint.ipynb [72.0 B]
  • 折线图绘制与显示-checkpoint.ipynb [72.0 B]
  • Pandas介绍-checkpoint.ipynb [72.0 B]
  • 课后作业及反馈-checkpoint.ipynb [1.8 KB]
  • 数据离散化-checkpoint.ipynb [69.6 KB]
  • 高级处理-缺失值处理-checkpoint.ipynb [72.0 B]
  • 缺失值处理-checkpoint.ipynb [72.0 B]
  • 数组间运算-checkpoint.ipynb [72.0 B]
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  • ndarray的基本操作-checkpoint.ipynb [44.5 KB]
  • 数组的运算-checkpoint.ipynb [172.3 KB]
  • 文件的读取和存储-checkpoint.ipynb [16.2 KB]
  • pandas 介绍-checkpoint.ipynb [72.0 B]
  • 高级处理-合并-checkpoint.ipynb [72.0 B]
  • ndarray介绍-checkpoint.ipynb [72.0 B]
  • 基本数据操作-checkpoint.ipynb [72.0 B]
  • 分组和聚合-checkpoint.ipynb [72.0 B]
  • 统计运算-checkpoint.ipynb [72.0 B]
  • 显示温度变化状况-checkpoint.ipynb [72.0 B]
  • 交叉表和透视表-checkpoint.ipynb [72.0 B]
  • ndarray运算-checkpoint.ipynb [72.0 B]
  • 常见图形的绘制-checkpoint.ipynb [72.0 B]
  • pandas的基本操作-checkpoint.ipynb [72.0 B]
  • 未命名-checkpoint.ipynb [72.0 B]
  • 数据的合并-checkpoint.ipynb [72.0 B]
  • 文件读取和存储-checkpoint.ipynb [72.0 B]
  • 分组与聚合-checkpoint.ipynb [72.0 B]
  • 高级处理-数据离散化-checkpoint.ipynb [72.0 B]
  • test.h5 [72.9 MB]
  • test.json [5.3 MB]
  • 文件读取和存储.ipynb [4.2 KB]
  • test.csv [7.3 KB]
  • 课后作业及反馈.ipynb [16.4 KB]
  • ._test.csv [4.0 KB]
  • 基本数据操作.ipynb [107.4 KB]
  • test_2.json [5.3 MB]
  • pandas 介绍.ipynb [65.1 KB]
  • ndarray运算.ipynb [13.3 KB]
  • 机器学习 (算法篇).exe [87.1 MB]
  • 机器学习 (科学计算库).exe [112.3 MB]
08_风控业务17 集
  • 11_特征衍生案例_.mp4 [27.3 MB]
  • 07_建模基本套路_.mp4 [57.4 MB]
  • 18_内容总结_.mp4 [53.6 MB]
  • 06_特征工程_特征选择_embeded_.mp4 [18.3 MB]
  • 12_特征衍生案例代码实现1_.mp4 [68.0 MB]
  • 15_移动应用大赛背景介绍_.mp4 [23.6 MB]
  • 14_特征衍生总结_.mp4 [9.4 MB]
  • 03_反欺诈规则可能用到的数据_.mp4 [13.8 MB]
  • 09_特征单调性和分布稳定性_.mp4 [47.7 MB]
  • 05_特征工程_特征选择_RFE_.mp4 [28.5 MB]
  • 16_移动应用大赛_特征工程_.mp4 [102.8 MB]
  • 04_特征工程_特征选择_.mp4 [50.9 MB]
  • 02_风控业务介绍_.mp4 [79.3 MB]
  • 17_移动应用大赛_模型融合_.mp4 [86.9 MB]
  • 08_建模基本套路总结_.mp4 [12.6 MB]
  • 10_特征单调性和分布稳定性总结_.mp4 [21.9 MB]
  • 13_特征衍生案例代码实现2_.mp4 [36.9 MB]
06_聚类分析14 集
  • 08_共享单车案例总结_.mp4 [44.1 MB]
  • 10_回归分析案例分析_.mp4 [24.7 MB]
  • 06_airbnb案例_.mp4 [18.1 MB]
  • 07_airbnb案例代码_.mp4 [53.2 MB]
  • 12_线性回归案例内容回顾_.mp4 [31.9 MB]
  • 14_线性回归套路总结_.mp4 [51.7 MB]
  • 03_聚类分析结果展示_.mp4 [26.4 MB]
  • 09_回归分析总结_.mp4 [50.8 MB]
  • 02_聚类分析介绍_.mp4 [44.4 MB]
  • 13_线性回归数据的基本处理_.mp4 [21.8 MB]
  • 11_内容总结_.mp4 [113.6 MB]
  • 15_社交电商线性回归分析总结_.mp4 [7.5 MB]
  • 04_聚类分析案例2_.mp4 [32.1 MB]
  • 05_聚类分析_年龄收入分群_.mp4 [26.4 MB]
07_电商数据17 集
  • 06_分类问题使用场景总结_.mp4 [27.2 MB]
  • 17_Pandas的API介绍3_.mp4 [67.1 MB]
  • 15_Pandas的API介绍1_.mp4 [88.0 MB]
  • 11_异常点检测isolationforest_.mp4 [69.1 MB]
  • 16_Pandas的API介绍2_.mp4 [35.0 MB]
  • 02_电商数据回归分析_.mp4 [30.1 MB]
  • 12_异常点检测isolationforest代码实现_.mp4 [29.1 MB]
  • 04_用户流失分析思路说明_.mp4 [32.0 MB]
  • 09_关联规则实现_.mp4 [19.5 MB]
  • 03_分类问题算法概述_.mp4 [41.6 MB]
  • 10_公式建模类算法总结_.mp4 [28.5 MB]
  • 08_关联规则基本概念_.mp4 [66.4 MB]
  • 13_异常点检测isolationforest可视化_.mp4 [41.7 MB]
  • 14_非结构化数据的处理_.mp4 [62.6 MB]
  • 07_优惠券使用预测_.mp4 [39.5 MB]
  • 01_内容回顾_.mp4 [22.4 MB]
  • 05_用户流失分析代码实现和结果分析_.mp4 [68.3 MB]
03_excel计算24 集
  • 10_常见图形_.mp4 [11.6 MB]
  • 18_门店会员明细表_.mp4 [30.0 MB]
  • 21_连带率计算完成_.mp4 [47.2 MB]
  • 12_会员存量增量分析_.mp4 [51.2 MB]
  • 05_match和index函数_.mp4 [13.6 MB]
  • 01_内容回顾_.mp4 [28.1 MB]
  • 09_Excel数据透视表_.mp4 [30.7 MB]
  • 19_地区会销比计算_.mp4 [94.5 MB]
  • 23_复购率计算实现_.mp4 [45.0 MB]
  • 13_会员等级分布_.mp4 [28.3 MB]
  • 20_连带率计算_.mp4 [26.9 MB]
  • 08_Excel文本处理函数_.mp4 [12.9 MB]
  • 06_vlookup和hlookup函数_.mp4 [27.4 MB]
  • 24_内容回顾_.mp4 [35.1 MB]
  • 11_会员分析概述_.mp4 [18.7 MB]
  • 02_excel基本功能介绍_.mp4 [37.6 MB]
  • 17_地区店均会员分析_2_.mp4 [37.9 MB]
  • 22_复购率计算分析_.mp4 [21.0 MB]
  • 14_会员整体占比分析_.mp4 [12.4 MB]
  • 04_excel逻辑函数_.mp4 [16.1 MB]
  • 07_indirect实现二级菜单_.mp4 [20.4 MB]
  • 16_地区店均会员分析_1_.mp4 [34.1 MB]
  • 15_线上线下会员增量对比_.mp4 [14.6 MB]
  • 03_excel计算函数_.mp4 [30.8 MB]
04_EXCEL-RFM11 集
  • 07_RFM的Python实现思路分析_.mp4 [50.4 MB]
  • 12_RFM结果通过excel保存处理_.mp4 [16.3 MB]
  • 05_RFM的excel实现_.mp4 [29.7 MB]
  • 09_RFM分群完成_.mp4 [32.9 MB]
  • 02_用户运营指标介绍_.mp4 [48.3 MB]
  • 08_RFM的数据处理实现&RFM划分思路_.mp4 [83.2 MB]
  • 11_RFM结果解读_.mp4 [53.6 MB]
  • 10_RFM分布可视化_.mp4 [30.6 MB]
  • 03_用户运营场景介绍_.mp4 [25.9 MB]
  • 04_用户运营相关模型_.mp4 [30.2 MB]
  • 06_会员运营模型_.mp4 [44.9 MB]
05_数据处理21 集
  • 11_数据处理_数据采样衡_.mp4 [46.5 MB]
  • 12_数据处理总结_.mp4 [14.4 MB]
  • 20_优衣库案例总结_.mp4 [46.4 MB]
  • 19_appstore数据分析_案例总结_.mp4 [42.6 MB]
  • 06_数据处理_数值型数据的归一化标准化_.mp4 [32.4 MB]
  • 21_内容回顾_.mp4 [11.7 MB]
  • 09_数据处理_分类特征数据处理_.mp4 [25.8 MB]
  • 04_数据处理_异常值重复值_.mp4 [27.7 MB]
  • 16_appstore数据分析_基本情况分析_.mp4 [19.6 MB]
  • 13_链家数据处理案例_.mp4 [44.2 MB]
  • 14_链家数据处理案例2_.mp4 [60.6 MB]
  • 07_数据处理_离散化_.mp4 [28.7 MB]
  • 03_数据处理_缺失值_.mp4 [34.8 MB]
  • 15_appstore数据分析_.mp4 [11.3 MB]
  • 17_appstore数据分析_价格单变量分析_.mp4 [36.8 MB]
  • 01_内容回顾_.mp4 [16.3 MB]
  • 18_appstore数据分析_数据可视化_.mp4 [27.9 MB]
  • 02_智能运营内容说明_.mp4 [20.0 MB]
  • 08_数据处理_离散化案例_.mp4 [33.2 MB]
  • 10_数据处理_样本分布不均衡_.mp4 [28.7 MB]
  • 05_数据处理_异常值重复值案例_.mp4 [35.5 MB]
day069 条
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day0410 条
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images100 条
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  • 框架关注.png [136.2 KB]
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  • 单agent多sink.png [245.4 KB]
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gitbook-plugin-search3 条
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online2 条
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scripts3 条
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  • collect_click.sh [302.0 B]
  • import_incremental.sh [2.0 KB]
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  • 耗时整理‖免费分享 cunlove.cn.png [4.0 KB]
  • ._QQ20190630-123306@2x.png [4.0 KB]
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  • 第五天课堂纪要.md [12.2 KB]
  • QQ20190630-123306@2x.png [948.5 KB]
  • ._第五天课堂纪要.pdf [4.0 KB]
  • ._QQ20190630-153602@2x.png [4.0 KB]
  • QQ20190630-111652@2x.png [324.3 KB]
  • 第五天课堂纪要.pdf [18.6 KB]
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  • QQ20190630-153602@2x.png [509.2 KB]
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01_视频15 集
  • 07_kafka的生产者与消费者_.mp4 [45.2 MB]
  • 08_kafka案例_.mp4 [58.8 MB]
  • 06_kafka介绍与存储原理_.mp4 [148.1 MB]
  • 10_Streamin在线内容召回实现_.mp4 [40.4 MB]
  • 13_新文章召回代码_.mp4 [16.5 MB]
  • 03_flume收集案例1_.mp4 [29.3 MB]
  • 15_spark优化了解_.mp4 [103.9 MB]
  • 11_在线内容召回结果实现_.mp4 [68.0 MB]
  • 05_flume实战_.mp4 [51.2 MB]
  • 14_在线更新程序定时更新_.mp4 [8.4 MB]
  • 01_复习_.mp4 [45.1 MB]
  • 04_flume收集案例2_.mp4 [74.9 MB]
  • 09_黑马推荐实时flume与kafka对接_.mp4 [54.3 MB]
  • 02_flume介绍_.mp4 [87.0 MB]
  • 12_新文章热门文章召回_.mp4 [51.8 MB]
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  • __init__.py [1.1 KB]
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  • reco_centor.py [12.2 KB]
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abtest5 条
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linear3 条
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scripts3 条
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  • start_kafka.sh [498.0 B]
  • import_incremental.sh [2.0 KB]
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  • 耗时整理‖免费分享 cunlove.cn.png [4.0 KB]
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01_视频13 集
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01_视频13 集
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linear1 条
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wide_and_deep1 条
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15619974671 条
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data16 条
  • adult.data [3.4 MB]
  • adult.test [1.7 MB]
  • nn_text_classification.py [2.2 KB]
  • demo.py [5.6 KB]
  • wide_deep.py [4.2 KB]
  • heima_ftrl.py [4.0 KB]
  • train_ctr_20190605.tfrecords [3.5 MB]
  • census_example.py [3.7 KB]
  • ctr_train_20190706.tfrecords [3.5 MB]
  • census_predict.py [10.6 KB]
  • recall_service.py [4.0 KB]
  • utils.py [4.0 KB]
  • redis_cache.py [3.9 KB]
  • reco_centor.py [12.2 KB]
  • sort_service.py [9.2 KB]
  • __init__.py [940.0 B]
scheduler2 条
  • main.py [1.3 KB]
  • update.py [1.1 KB]
scripts3 条
  • collect_click.sh [302.0 B]
  • import_incremental.sh [2.0 KB]
  • start_kafka.sh [498.0 B]
RSPaper7 条
  • paragraph_vector.pdf [286.1 KB]
  • bengio03a.pdf [136.8 KB]
  • 在线最优化求解(Online Optimization)-冯扬.pdf [961.1 KB]
  • 1301.3781.pdf [223.4 KB]
  • hlww-2018124152810.pdf [1.2 MB]
  • 百面机器学习.pdf [25.2 MB]
  • 黑马头条推荐系统完整课件V3.0.zip [65.2 MB]
01_视频11 集
  • 02_推荐缓存实现_.mp4 [99.8 MB]
  • 08_TF的图与节点OP特点_.mp4 [80.0 MB]
  • 05_模型排序问题解决以及添加推荐中心_.mp4 [65.5 MB]
  • 04_LR模型排序测试_.mp4 [144.7 MB]
  • 10_张量与变量_.mp4 [68.7 MB]
  • 03_推荐缓存测试_.mp4 [29.1 MB]
  • 06_推荐系统与深度学习介绍_.mp4 [87.9 MB]
  • 01_复习_.mp4 [34.9 MB]
  • 11_案例：线性回归实现与训练_.mp4 [71.1 MB]
  • 09_会话_.mp4 [39.1 MB]
  • 07_TF数据流图_.mp4 [34.0 MB]
04_资料8 条
  • 第七天课堂纪要.pdf [144.8 KB]
  • ._QQ20190703-175158@2x.png [4.0 KB]
  • 耗时整理‖免费分享 cunlove.cn.png [234.1 KB]
  • QQ20190703-165144@2x.png [493.2 KB]
  • 第七天课堂纪要.md [6.4 KB]
  • ._第七天课堂纪要.md [4.0 KB]
  • ._第七天课堂纪要.pdf [4.0 KB]
  • ._QQ20190703-165144@2x.png [4.0 KB]
day0410 条
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images100 条
  • 网页pagerank.png [570.7 KB]
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  • 黑马头条宣传.png [761.2 KB]
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  • 倾斜解决方案2.png [500.0 KB]
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  • groupbykey.png [838.2 KB]
  • 随机值张量.png [126.8 KB]
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  • hadoop启动好的.png [248.7 KB]
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  • 年份分桶.png [184.0 KB]
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  • tfdataset格式.png [65.3 KB]
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  • tensors_flowing.gif [9.5 MB]
  • 用户关联结果2.png [160.0 KB]
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  • 推荐算法总结.png [465.5 KB]
  • 两类数据分类.png [110.5 KB]
  • 查看倾斜.png [292.4 KB]
  • spark启动好的.png [350.4 KB]
  • 复杂数据2.png [247.3 KB]
  • softmax展开.png [58.3 KB]
  • agent.png [103.1 KB]
  • 用户画像流程作用.png [68.8 KB]
  • 消费者设计.png [275.3 KB]
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  • 感知机公式.png [43.0 KB]
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  • 特征处理原则.png [94.4 KB]
  • kafka.png [36.8 KB]
  • 系统耦合高.png [117.7 KB]
  • 感知机.png [49.8 KB]
  • profucer写数据过程.png [221.7 KB]
  • 流式计算与批量计算的对比.png [276.0 KB]
  • 实时在线flume设置.png [45.5 KB]
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  • Textrank原理.png [56.2 KB]
  • 网络结构.png [113.6 KB]
  • ML与DL关系.png [445.8 KB]
  • 训练样本特正处理3.png [372.9 KB]
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  • 运行的APP.png [357.1 KB]
  • 鸢尾花网络模型.png [216.9 KB]
  • 离线在线计算.png [116.1 KB]
  • 多agent.png [250.0 KB]
  • LR简单模型特征.png [388.4 KB]
  • 模型存放目录.png [129.0 KB]
  • softmax公式.png [27.9 KB]
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  • LR.png [148.0 KB]
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  • 用户原始数据.png [96.8 KB]
  • word2vecnn.png [119.6 KB]
  • 在线目录.png [14.1 KB]
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  • tensorflowgithub.png [164.5 KB]
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  • 表截图.png [106.3 KB]
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  • records.png [247.0 KB]
  • 用户主题词爆炸.png [229.6 KB]
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  • 数据倾斜方案1.png [717.5 KB]
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images2 条
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fontawesome5 条
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gitbook-plugin-livereload1 条
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gitbook-plugin-fontsettings2 条
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fonts81 条
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  • KaTeX_SansSerif-Italic.eot [30.6 KB]
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gitbook-plugin-highlight2 条
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gitbook-plugin-search5 条
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online2 条
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abtest5 条
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setting2 条
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server6 条
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summary2 条
  • events.out.tfevents.1561764557.hadoop-master [690.0 B]
  • demo.py [4.5 KB]
.ipynb_checkpoints13 条
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scheduler2 条
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inspectionProfiles1 条
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dictionaries8 条
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  • deployment.xml [771.0 B]
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  • misc.xml [852.0 B]
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  • encodings.xml [135.0 B]
  • toutiao_project.iml [603.0 B]
scripts3 条
  • import_incremental.sh [2.0 KB]
  • start_kafka.sh [498.0 B]
  • collect_click.sh [302.0 B]
scheduler2 条
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  • main.py [1.3 KB]
dictionaries1 条
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inspectionProfiles8 条
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  • deployment.xml [771.0 B]
  • modules.xml [282.0 B]
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  • encodings.xml [135.0 B]
  • workspace.xml [54.3 KB]
  • remote-mappings.xml [491.0 B]
  • misc.xml [852.0 B]
setting1 条
  • logging.py [508.0 B]
.ipynb_checkpoints12 条
  • merge_data-checkpoint.ipynb [72.0 B]
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scripts2 条
  • import_incremental.sh [2.0 KB]
  • collect_click.sh [302.0 B]
01_视频12 集
  • 06_模型训练3_.mp4 [35.3 MB]
  • 08_模型预测结果_.mp4 [35.1 MB]
  • 02_基于内容召回_.mp4 [79.1 MB]
  • 09_用户特征中心存储_.mp4 [21.9 MB]
  • 01_复习_.mp4 [69.2 MB]
  • 11_离线任务总结_.mp4 [11.6 MB]
  • 10_特征中心定时更新_.mp4 [23.7 MB]
  • 07_模型问题解决与特征中心_.mp4 [58.9 MB]
  • 04_模型训练1_.mp4 [84.3 MB]
  • 12_实时计算业务介绍_.mp4 [42.3 MB]
  • 05_模型训练2_.mp4 [137.3 MB]
  • 03_离线召回定时更新_.mp4 [20.2 MB]
images100 条
  • 测试样本构造.png [304.7 KB]
  • OP名字修改.png [29.6 KB]
  • 交叉熵损失公式.png [22.7 KB]
  • abtest与推荐中心逻辑.png [75.3 KB]
  • count结果.png [117.0 KB]
  • 原始ALS数据.png [150.3 KB]
  • 交叉损失理解.png [121.1 KB]
  • premadeestirmaot.png [90.7 KB]
  • 数据流图.png [164.2 KB]
  • 鸢尾花.png [3.4 MB]
  • 感知机.png [49.8 KB]
  • textrank词性.png [480.4 KB]
  • 区别.png [162.8 KB]
  • 复杂数据2.png [247.3 KB]
  • ROC曲线.png [64.1 KB]
  • softmax回归.png [112.2 KB]
  • 单agent多sink.png [245.4 KB]
  • TFIDF结果2.png [111.6 KB]
  • 合并用户文章.png [200.1 KB]
  • sqoop导入hadoop文件数据.png [128.8 KB]
  • 用户画像流程作用.png [68.8 KB]
  • flume外部结构.png [89.1 KB]
  • spark启动好的.png [350.4 KB]
  • 与或问题.png [38.5 KB]
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images100 条
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day0714 条
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01_视频12 集
  • 03_文章画像计算存储_.mp4 [36.8 MB]
  • 07_文章向量计算_.mp4 [25.4 MB]
  • 01_作业讲解_.mp4 [65.8 MB]
  • 08_文章向量保存_.mp4 [42.4 MB]
  • 10_相似度计算介绍_.mp4 [24.9 MB]
  • 04_离线更新添加_.mp4 [74.7 MB]
  • 12_相似度结果存储_.mp4 [42.0 MB]
  • 09_文章向量保存2_.mp4 [46.9 MB]
  • 11_LSH原理与实现_.mp4 [123.0 MB]
  • 05_离线增量更新_.mp4 [23.1 MB]
  • 06_word2vec介绍与词向量训练保存_.mp4 [97.3 MB]
  • 02_文章关键词与主题词计算_.mp4 [58.7 MB]
scripts2 条
  • import_incremental.sh [2.0 KB]
  • collect_click.sh [302.0 B]
inspectionProfiles1 条
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dictionaries8 条
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  • deployment.xml [771.0 B]
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  • modules.xml [282.0 B]
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  • encodings.xml [135.0 B]
.ipynb_checkpoints4 条
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  • merge_data.ipynb [46.2 KB]
  • __init__.py [1.4 KB]
  • update_article(1).py [8.4 KB]
setting1 条
  • logging.py [508.0 B]
scheduler2 条
  • update.py [351.0 B]
  • main.py [783.0 B]
style.mindnodestyle4 条
  • ._contents.xml [4.0 KB]
  • metadata.plist [395.0 B]
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  • contents.xml [6.2 KB]
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  • favicon.ico [4.2 KB]
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style.mindnodestyle4 条
  • ._contents.xml [4.0 KB]
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QuickLook2 条
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resources34 条
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01_视频13 集
  • 04_统计与神经网络语言模型_.mp4 [91.2 MB]
  • 15_总结_.mp4 [38.8 MB]
  • 11_传统CTR排序演化图以及介绍_.mp4 [20.9 MB]
  • 05_word2vec介绍_.mp4 [5.7 MB]
  • 09_黑马头条训练样本存储tfrecords1_.mp4 [78.5 MB]
  • 08_tfrecords文件深度训练流程方案_.mp4 [31.9 MB]
  • 06_wor2vec的前向计算与反向传播计算_.mp4 [43.2 MB]
  • 14_特征交叉与分桶案例_.mp4 [35.1 MB]
  • 07_文本分类案例与词向量观察_.mp4 [105.1 MB]
  • 13_特征交叉与分桶_.mp4 [21.7 MB]
  • 10_黑马头条训练样本存储tfrecords2_.mp4 [34.5 MB]
  • 01_复习_.mp4 [73.7 MB]
  • 12_传统CTR排序演化图以及介绍2_.mp4 [57.2 MB]
dictionaries1 条
  • huxinghui.xml [88.0 B]
inspectionProfiles8 条
  • Project_Default.xml [790.0 B]
  • remote-mappings.xml [491.0 B]
  • deployment.xml [771.0 B]
  • workspace.xml [56.9 KB]
  • toutiao_project.iml [603.0 B]
  • misc.xml [852.0 B]
  • encodings.xml [135.0 B]
  • modules.xml [282.0 B]
scheduler2 条
  • update.py [1.1 KB]
  • main.py [1.3 KB]
scripts3 条
  • collect_click.sh [302.0 B]
  • start_kafka.sh [498.0 B]
  • import_incremental.sh [2.0 KB]
server6 条
  • redis_cache.py [3.9 KB]
  • sort_service.py [3.1 KB]
  • reco_centor.py [12.2 KB]
  • utils.py [4.0 KB]
  • __init__.py [925.0 B]
  • recall_service.py [4.0 KB]
setting2 条
  • default.py [2.4 KB]
  • logging.py [1.2 KB]
abtest5 条
  • user_reco_pb2_grpc.py [2.1 KB]
  • user_reco.proto [738.0 B]
  • user_reco_pb2.py [11.8 KB]
  • grpc_test.py [1.7 KB]
  • routing.py [6.0 KB]
.ipynb_checkpoints12 条
  • word2vec-checkpoint.ipynb [72.0 B]
  • update_recall-checkpoint.ipynb [26.5 KB]
  • lr_sort-checkpoint.ipynb [72.0 B]
  • merge_data-checkpoint.ipynb [72.0 B]
  • online_sort-checkpoint.ipynb [72.0 B]
  • user_profile-checkpoint.ipynb [72.0 B]
  • lr_sort.ipynb [189.9 KB]
  • word2vec.ipynb [25.7 KB]
  • update_recall.ipynb [30.5 KB]
  • online_sort.ipynb [9.0 KB]
  • user_profile.ipynb [20.8 KB]
  • merge_data.ipynb [46.2 KB]
data2 条
  • adult.test [1.7 MB]
  • adult.data [3.4 MB]
linear3 条
  • …（层级过深，已停止）
  • events.out.tfevents.1561764557.hadoop-master [690.0 B]
  • events.out.tfevents.1561765617.hadoop-master [650.0 B]
  • events.out.tfevents.1561766113.hadoop-master [650.0 B]
linear1 条
  • …（层级过深，已停止）
text_embedding36 条
  • events.out.tfevents.1561869077.hadoop-master [148.8 MB]
  • model.ckpt-2817137.index [575.0 B]
  • model.ckpt-2636266.data-00001-of-00002 [40.6 KB]
  • model.ckpt-2636266.index [575.0 B]
  • model.ckpt-2726691.data-00000-of-00002 [1.9 MB]
  • model.ckpt-2557167.data-00000-of-00002 [1.9 MB]
  • model.ckpt-2817137.data-00001-of-00002 [40.6 KB]
  • model.ckpt-2726691.meta [19.4 MB]
  • model.ckpt-2636266.data-00000-of-00002 [1.9 MB]
  • model.ckpt-2817137.meta [19.4 MB]
  • checkpoint [289.0 B]
  • model.ckpt-2726691.index [575.0 B]
  • graph.pbtxt [73.5 MB]
  • model.ckpt-2636266.meta [19.4 MB]
  • model.ckpt-2466253.data-00001-of-00002 [40.6 KB]
  • model.ckpt-2466253.data-00000-of-00002 [1.9 MB]
  • model.ckpt-2557167.data-00001-of-00002 [40.6 KB]
  • model.ckpt-2466253.meta [19.4 MB]
  • model.ckpt-2726691.data-00001-of-00002 [40.6 KB]
  • model.ckpt-2557167.meta [19.4 MB]
  • model.ckpt-2557167.index [575.0 B]
  • model.ckpt-2817137.data-00000-of-00002 [1.9 MB]
  • model.ckpt-2466253.index [575.0 B]
  • ctr_train_20190706.tfrecords [3.5 MB]
  • train_ctr_20190605.tfrecords [3.5 MB]
  • census_example.py [3.7 KB]
  • nn_text_classification.py [2.2 KB]
  • demo.py [5.6 KB]
  • census_predict.py [10.6 KB]
  • update_user.py [9.3 KB]
  • update_recall.py [9.5 KB]
  • update_article.py [12.5 KB]
  • text_class.py [2.3 KB]
  • update_feature.py [4.7 KB]
  • __init__.py [2.4 KB]
  • hbaset.py [536.0 B]
online2 条
  • __init__.py [1.1 KB]
  • online_update.py [5.7 KB]
data6 条
  • adult.data [3.4 MB]
  • adult.test [1.7 MB]
  • 黑马头条推荐系统完整课件V3.0.zip [65.2 MB]
  • 归档.zip [622.1 KB]
  • demo.py [5.6 KB]
  • 黑马头条推荐分布式&单机版大数据环境使用教程.pdf [689.6 KB]
视频17 集
  • 17，物品画像的关键词权重提取代码实现_.mp4 [65.2 MB]
  • 2，基于模型的协同过滤推荐_.mp4 [50.3 MB]
  • 3，基于模型的协同过滤代码思路整理_.mp4 [26.6 MB]
  • 12，BiasSVD原理介绍及其代码实现_.mp4 [10.7 MB]
  • 11，LFM代码实现_.mp4 [25.0 MB]
  • 9，基于矩阵分解的发展史_.mp4 [51.0 MB]
  • 16，获取电影数据集代码实现_.mp4 [33.5 MB]
  • 14锛宼fidf浠嬬粛_.mp4 [35.0 MB]
  • 5，基于模型的协同过滤代码实现_.mp4 [76.9 MB]
  • 13，基于内容的推荐算法介绍_.mp4 [23.8 MB]
  • 4，虚拟机环境配置_.mp4 [17.0 MB]
  • 8锛屼笂鍗堝皬缁揰.mp4 [15.4 MB]
  • 10，LFM算法原理介绍_.mp4 [14.2 MB]
  • 15，获取电影数据集_.mp4 [34.8 MB]
  • 18锛屾€荤粨_.mp4 [45.4 MB]
  • 7，交替最小二乘法原理讲解_.mp4 [10.1 MB]
  • 6，数据划分，准确率评估实现_.mp4 [92.7 MB]
资料4 条
  • movies.csv [482.8 KB]
  • tags.csv [115.9 KB]
  • ratings.csv [2.4 MB]
  • 概述.txt [836.0 B]
pdf3 条
  • day02-推荐系统算法.xmind [61.5 KB]
  • day01-推荐系统简介.xmind [87.3 KB]
  • day03、day04-hadoop.xmind [140.8 KB]
img35 条
  • 1.png [16.1 KB]
  • zkshell1.png [56.5 KB]
  • dist4.png [6.2 KB]
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hdfs_read_write54 条
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类库17 条
  • java-json.jar [82.7 KB]
  • spark-streaming_2.11-2.3.0.jar [2.1 MB]
  • commons-lang3-3.7.jar [487.9 KB]
  • spark-streaming-kafka-0-8-assembly_2.11-2.3.0.jar [11.7 MB]
  • commons-lang3-3.8.jar [490.1 KB]
  • spark-streaming-kafka-0-8-assembly_2.11-2.1.1.jar [10.8 MB]
  • leiningen-2.8.1-standalone.jar [12.9 MB]
  • mysql-connector-java-5.1.36.jar [949.2 KB]
  • scala-library-2.11.8.jar [5.5 MB]
  • commons-lang3-3.8.1.jar [490.1 KB]
  • mysql-connector-java-5.1.47-bin.jar [983.9 KB]
  • spark-streaming-flume-assembly_2.11-2.3.0.jar [2.3 MB]
  • Miniconda3-4.3.14-Linux-x86_64.sh [33.1 MB]
  • kafka_2.11-1.1.0.tgz [54.3 MB]
  • Python-2.7.14.tgz [16.4 MB]
  • 讲义_20190616.zip [56.5 MB]
  • 推荐系统资料-详细.zip [152.8 MB]
视频17 集
  • 9锛屼笂鍗堝皬缁揰.mp4 [60.0 MB]
  • 8，数据分析案例_.mp4 [30.6 MB]
  • 16，内部表和外部表_.mp4 [24.4 MB]
  • 10锛屼粈涔堟槸hive_.mp4 [14.4 MB]
  • 14，hive的安装部署_.mp4 [44.3 MB]
  • 15，hive的shell操作_.mp4 [28.5 MB]
  • 4，mapreduce原理介绍_.mp4 [60.7 MB]
  • 6锛宧dfs鐨勮鍐欐祦绋媉.mp4 [79.8 MB]
  • 11，hive的架构_.mp4 [17.0 MB]
  • 18锛屽姩鎬佸垎鍖篲.mp4 [11.8 MB]
  • 2，topN实现_.mp4 [67.6 MB]
  • 12，Hive与传统数据库对比_.mp4 [14.9 MB]
  • 3锛宼opN璋冭瘯_.mp4 [21.1 MB]
  • 17锛屽垎鍖鸿〃_.mp4 [44.5 MB]
  • 13，hive的数据模型_.mp4 [27.8 MB]
  • 7，大数据与互联网产品结合_.mp4 [34.1 MB]
  • 思路.txt [2.4 KB]
pics48 条
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  • s6.PNG [102.5 KB]
  • kafka_13.png [222.3 KB]
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  • kafka_10.png [238.6 KB]
  • 1540350201715.png [78.7 KB]
  • kafka_2.png [22.7 KB]
  • 1540347389671.png [52.7 KB]
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  • kafka_12.png [147.0 KB]
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  • kafka_16.png [51.2 KB]
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  • kafka_5.png [253.0 KB]
  • kafka_7.png [393.8 KB]
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  • 1540350245310.png [223.5 KB]
  • kafka_17.png [129.5 KB]
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a116 条
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  • README.md [498.0 B]
  • SUMMARY.md [3.3 KB]
资料3 条
  • SecureCRT keygen.zip [423.6 KB]
  • HBase.xmind [140.8 KB]
  • Spark-core.xmind [111.9 KB]
前天的spark-core资料3 条
  • access.log [2.9 MB]
  • 20090121000132.394251.http(1).format [1.9 MB]
  • ip.txt [13.7 MB]
视频11 集
  • 3锛孒Base鐨勭粍浠禵.mp4 [139.9 MB]
  • 4，RDD的概念和RDD的创建_.mp4 [113.7 MB]
  • 2锛孒appyBase鎿嶄綔Hbase_.mp4 [73.6 MB]
  • 9，pycharm连接远程centos环境准备_.mp4 [13.0 MB]
  • 11，spark-core实现日志分析_.mp4 [116.6 MB]
  • 8，action算子和两类算子的执行_.mp4 [16.7 MB]
  • 4，spark介绍及其local模式启动_.mp4 [54.6 MB]
  • 12，ip地址查询实现_.mp4 [148.0 MB]
  • 5，RDD的两种常用操作_.mp4 [12.9 MB]
  • 10，spark实现wordcount_.mp4 [87.4 MB]
  • 1.png [226.5 KB]
视频14 集
  • 2，项目思路整理和数据集切分_.mp4 [38.6 MB]
  • 15，完成商品的精选及其总结_.mp4 [100.6 MB]
  • 3锛岀敵璇穝park鐨勮祫婧恄.mp4 [31.2 MB]
  • 6，raw_sample数据的读取和处理_.mp4 [94.1 MB]
  • 7，ad_feature的数据读取和处理_.mp4 [26.5 MB]
  • 10，user_profile缺失值处理-低维数据转高维数据_.mp4 [53.3 MB]
  • 13，建立广告类别和广告id的匹配关系_.mp4 [73.1 MB]
  • 12，CTR模型训练-实现_.mp4 [26.3 MB]
  • 14，结合redis完成商品召回_.mp4 [30.9 MB]
  • 9，user_profile缺失值处理-利用随机森林对缺失值进行预测_.mp4 [128.4 MB]
  • 11，CTR模型训练-数据准备_.mp4 [56.1 MB]
  • 5，保存数据模型及其召回商品到redis_.mp4 [32.8 MB]
  • 8锛屼笂鍗堝皬缁揰.mp4 [11.0 MB]
  • 4，spark实现数据的读取和评分数据的构建_.mp4 [132.6 MB]
img18 条
  • word2vec1.png [32.6 KB]
  • word2vec2.png [34.4 KB]
  • 1545630651922.png [88.0 KB]
  • recommend2.png [145.1 KB]
  • recommend1.png [321.1 KB]
  • word2vec3.png [38.8 KB]
  • 1545630559725.png [104.3 KB]
  • chrome_start.png [3.7 KB]
  • chapter2.md [32.9 KB]
  • chapter5.md [9.3 KB]
  • chapter9.md [10.2 KB]
  • chapter4.md [50.9 KB]
  • chapter8.md [20.7 KB]
  • chapter6.md [13.1 KB]
  • chapter3.md [63.9 KB]
  • chapter1.md [1.9 KB]
  • chapter7.md [26.7 KB]
  • chapter10.md [8.6 KB]
img104 条
  • algorithm1.png [146.7 KB]
  • similarity_calc6.png [56.5 KB]
  • 协同推荐评分数据集.jpg [65.8 KB]
  • similarity_calc4.png [73.9 KB]
  • 推荐流程.png [16.9 KB]
  • Rocchio-3.jpg [28.6 KB]
  • recommend6.png [36.7 KB]
  • 混合推荐方法.jpeg [142.4 KB]
  • 并行式-混杂式.jpeg [120.8 KB]
  • 流水线式-级联式.jpeg [122.8 KB]
  • algorithm7.png [308.0 KB]
  • 相似度计算示例.png [23.9 KB]
  • userprofile1.jpeg [33.2 KB]
  • 基础CB推荐算法.jpg [18.2 KB]
  • itemcf2.png [113.8 KB]
  • similarity_calc2.png [255.8 KB]
  • spark01.PNG [18.5 KB]
  • similarity_calc8.png [42.6 KB]
  • 并行式-加权式.jpeg [129.9 KB]
  • usercf1.png [71.8 KB]
  • similarity_calc16.png [26.8 KB]
  • similarity_calc7.png [27.7 KB]
  • 推荐知识库示例.jpeg [160.7 KB]
  • RS基础技术架构.png [1.1 MB]
  • lambda6.png [85.4 KB]
  • 整体式-特征混合.jpeg [105.2 KB]
  • similarity_calc13.png [55.6 KB]
  • algorithm5.png [187.2 KB]
  • als1.png [183.0 KB]
  • itemcf1.png [103.4 KB]
  • similarity_calc10.png [64.9 KB]
  • algorithm2.png [146.7 KB]
  • recommend5.png [250.6 KB]
  • 修正的余弦相似度公式.jpg [51.8 KB]
  • recommend2.png [61.4 KB]
  • 整体式-特征补充.jpeg [135.1 KB]
  • algorithm3.png [94.8 KB]
  • 基于用户的预测公式.jpg [18.6 KB]
  • recommend7.jpeg [13.1 KB]
  • algorithm6.png [238.0 KB]
  • 隐因子模型介绍.jpg [158.2 KB]
  • lambda5.png [58.1 KB]
  • lambda2.png [199.9 KB]
  • 1545049355235.png [86.6 KB]
  • 并行式混合方法.jpeg [88.8 KB]
  • Rocchio-1.jpg [18.5 KB]
  • usercf2.png [22.2 KB]
  • od.png [10.6 KB]
  • 用户画像2.jpg [45.0 KB]
  • spark02.PNG [25.1 KB]
  • 挖掘频繁项集.png [102.8 KB]
  • 整体式-特征组合.jpeg [105.2 KB]
  • similarity_calc3.png [78.0 KB]
  • firststart.png [226.3 KB]
  • 整体式混合方法.jpeg [103.6 KB]
  • similarity_calc14.png [24.5 KB]
  • user-itemMatrix3.png [37.9 KB]
  • graph1.png [57.8 KB]
  • Pearson相关系数公式.jpg [29.0 KB]
  • algorithm4.png [101.5 KB]
  • firststart1.png [537.2 KB]
  • od2.png [4.0 KB]
  • lambda7.png [225.2 KB]
  • recommend1.png [501.9 KB]
  • similarity_calc1.png [21.5 KB]
  • 并行式-切换式.jpeg [153.7 KB]
  • Rocchio-2.jpg [23.7 KB]
  • 基于物品的预测公式.jpg [22.5 KB]
  • lambda4.png [97.0 KB]
  • RS基础业务架构.png [343.2 KB]
  • lambda1.png [136.6 KB]
  • knn2.png [56.7 KB]
  • 流水线式-层叠式.jpeg [124.1 KB]
  • usercf3.png [4.5 KB]
  • similarity_calc12.png [104.2 KB]
  • similarity_calc5.png [241.9 KB]
  • similarity_calc15.png [24.1 KB]
  • recommend4.png [103.7 KB]
  • recommend3.png [218.1 KB]
  • 决策树.jpg [227.4 KB]
  • lambda3.png [167.0 KB]
  • user-itemMatrix4.png [51.1 KB]
  • CF介绍.png [178.0 KB]
  • similarity_calc11.png [64.4 KB]
  • user-itemMatrix2.png [86.2 KB]
  • similarity_calc9.png [56.7 KB]
  • firststart2.png [564.2 KB]
  • user-itemMatrix.png [24.9 KB]
  • knn1.png [63.8 KB]
  • 流水线式混合方法.jpeg [65.4 KB]
  • 推荐系统.md [216.0 KB]
  • 推荐算法.md [12.7 KB]
  • 07_根据用户行为数据创建ALS模型并召回商品.md [26.0 KB]
  • 06_个性化电商广告推荐系统介绍.md [6.1 KB]
  • 08_CTR预估数据准备.md [71.9 KB]
  • 05_ 推荐系统冷启动问题.md [1.5 KB]
  • 10_离线推荐处理.md [9.6 KB]
  • 03_推荐系统架构设计.md [2.0 KB]
  • 09_逻辑回归实现CTR预估.md [66.9 KB]
  • 11_实时推荐.md [11.7 KB]
  • 02_ 推荐系统评估.md [3.2 KB]
  • 离线推荐处理.md [12.1 KB]
  • 04_推荐算法.md [12.9 KB]
  • 01_推荐系统简介.md [3.7 KB]
code2 条
  • hbasemanager.py [1.1 KB]
  • happybase_demo.py [3.4 KB]
img47 条
  • 2012121416.jpeg [52.9 KB]
  • 2017-12-27_192040.jpg [32.1 KB]
  • table2.png [76.7 KB]
  • 2017-12-27_173407.jpg [113.7 KB]
  • spark-hadoop2.png [110.9 KB]
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pics48 条
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hdfs_read_write52 条
  • e.jpg [156.9 KB]
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  • image-yarn.png [656.7 KB]
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  • image-mapreduce3.png [1.1 MB]
  • mp3.png [666.8 KB]
  • image-大数据行业应用.png [526.8 KB]
  • hadoop-生态.png [396.0 KB]
  • hadoop-yarn3.png [96.4 KB]
  • image-mapreduce2.png [668.1 KB]
  • image-hadoop1.png [433.1 KB]
  • mp5.png [863.2 KB]
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  • image-MapReduce4.png [335.6 KB]
  • hadoop-yarn.jpg [34.5 KB]
  • image-MapReduce5.png [334.6 KB]
  • mr_result.png [38.1 KB]
  • image-大数据应用3.png [1008.5 KB]
  • image-bigdata01.png [546.4 KB]
  • hadoop-hdfs1.png [29.3 KB]
  • mp1.png [991.2 KB]
  • yarn_architecture.gif [32.3 KB]
  • image-mapreduce1.png [327.3 KB]
  • image-yarn2.png [652.6 KB]
  • yarn4.png [70.9 KB]
  • image-大数据应用2.png [1.3 MB]
  • image-mapreduce.png [524.6 KB]
  • mp4.png [461.0 KB]
  • hadoop-hdfsarchitecture.png [39.6 KB]
  • ha1.0.md [150.0 B]
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  • ha.md [115.0 B]
  • ha2.4.md [1.9 KB]
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资料4 条
  • access.log [2.9 MB]
  • ip.txt [13.7 MB]
  • user.txt [150.0 B]
  • 20090121000132.394251.http.format [1.9 MB]
pics66 条
  • kafka_14.png [91.6 KB]
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  • kafka_15.png [56.2 KB]
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  • 1540350201715.png [78.7 KB]
  • kafka_6.png [60.6 KB]
  • kafka_17.png [129.5 KB]
  • kafka_3.png [83.6 KB]
  • 1540349678122.png [37.2 KB]
  • s3.PNG [86.2 KB]
  • kafka_12.png [147.0 KB]
  • 1540350674304(1).png [21.2 KB]
  • 1540350201715(1).png [78.7 KB]
  • kafka_16(1).png [51.2 KB]
  • 1540347422756(1).png [102.2 KB]
  • kafka_13.png [222.3 KB]
  • 1540350245310(1).png [223.5 KB]
  • kafka_11(1).png [78.6 KB]
  • 1540347375394.png [52.7 KB]
  • kafka_14(1).png [91.6 KB]
  • s1.PNG [19.0 KB]
  • spark3.PNG [90.6 KB]
  • s5.PNG [143.6 KB]
  • s8.PNG [203.5 KB]
  • kafka_4(1).png [60.6 KB]
  • spark2.PNG [12.0 KB]
  • kafka_15(1).png [56.2 KB]
  • kafka_13(1).png [222.3 KB]
  • 1540347389671.png [52.7 KB]
  • 宽依赖和窄依赖.png [250.5 KB]
  • kafka_11.png [78.6 KB]
  • 1540347254561(1).png [32.7 KB]
  • 1540347389671(1).png [52.7 KB]
  • s1.5.md [2.7 KB]
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a118 条
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  • ml04.png [103.7 KB]
  • kafka_3.png [83.6 KB]
  • 1540350260244.png [223.5 KB]
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  • 宽依赖和窄依赖.png [250.5 KB]
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  • 1540347375394.png [52.7 KB]
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  • ml30.png [260.2 KB]
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  • 1540350201715.png [78.7 KB]
  • kafka_6.png [60.6 KB]
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  • kafka_4.png [60.6 KB]
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  • kafka_7.png [393.8 KB]
  • kafka_10.png [238.6 KB]
  • ml37.png [45.5 KB]
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  • ml02.png [119.5 KB]
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  • 1540347422756.png [102.2 KB]
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  • ml36.png [187.9 KB]
  • ml13.png [25.2 KB]
  • s1.6.md [3.1 KB]
  • ml1.1.md [4.4 KB]
  • s1.7.md [4.0 KB]
  • s1.2.md [791.0 B]
  • ml1.4.md [3.6 KB]
  • s1.4 - 副本.md [7.8 KB]
  • s1.5.md [4.5 KB]
  • s1.0.md [339.0 B]
  • ml1.3.md [5.0 KB]
  • s1.1.md [2.9 KB]
  • ml1.0.md [299.0 B]
  • s1.4.md [9.0 KB]
  • ml1.2.md [8.6 KB]
  • s1.3.md [1.6 KB]
  • s.md [115.0 B]
  • SUMMARY.md [3.3 KB]
  • README.md [498.0 B]
  • 推荐系统资料-详细.zip [152.8 MB]
  • 项目.xmind [106.2 KB]
.ipynb_checkpoints1 条
  • ratings.csv [2.4 MB]
视频114 集
  • 5，推荐系统设计_.mp4 [56.2 MB]
  • 4，推荐系统和web项目的区别_.mp4 [21.3 MB]
  • 6，推荐系统的算法流程介绍_.mp4 [49.4 MB]
  • 2，课程整体介绍_.mp4 [6.4 MB]
  • 14，推荐系统评估_.mp4 [38.5 MB]
  • 15，推荐系统的冷启动问题_.mp4 [72.5 MB]
  • 3锛屾帹鑽愭槸浠€涔坃.mp4 [40.5 MB]
  • 12，针对于连续型数据的评分算法_.mp4 [23.4 MB]
  • 11，基于用户和基于物品的推荐案例完成_.mp4 [104.6 MB]
  • 13，User-Based的评分预测案例实现_.mp4 [114.5 MB]
  • 1锛屽涔犳柟娉昣.mp4 [4.5 MB]
  • 8，相似度算法介绍_.mp4 [56.8 MB]
  • 10锛屾€荤粨_.mp4 [57.7 MB]
  • 9，相似度计算案例-1_.mp4 [37.5 MB]
视频14 集
  • 8，数据去重_.mp4 [11.1 MB]
  • 2锛孲parkSQL浠嬬粛_.mp4 [64.2 MB]
  • 7锛屼笂鍗堝皬缁揰.mp4 [16.2 MB]
  • 6，动态json数据的读取和操作_.mp4 [30.7 MB]
  • 13，SparkStreaming实现WordCount_.mp4 [31.5 MB]
  • 9锛岀己澶卞€煎鐞哶.mp4 [74.3 MB]
  • 5，静态json数据的读取和操作_.mp4 [29.9 MB]
  • 3，创建DataFrame的一些方法_.mp4 [59.8 MB]
  • 16，数据集介绍_.mp4 [64.8 MB]
  • 15，状态操作-windows_.mp4 [48.1 MB]
  • 11锛孲parkStreaming浠嬬粛_.mp4 [28.0 MB]
  • 17锛屾€荤粨_.mp4 [254.6 MB]
  • 12锛孲parkStreaming鐨勭粍浠禵.mp4 [14.8 MB]
  • 10锛屽紓甯稿€煎鐞哶.mp4 [29.6 MB]
资料7 条
  • ad_feature.csv [29.8 MB]
  • user_profile.csv [22.9 MB]
  • raw_sample.csv [1.0 GB]
  • SparkSQL.xmind [89.3 KB]
  • SparkStreaming.xmind [63.9 KB]
  • Spark-core.xmind [152.2 KB]
  • 项目.xmind [64.0 KB]
视频13 集
  • 9，Hbase的环境配置_.mp4 [51.9 MB]
  • 1锛屽弽棣堟€荤粨_.mp4 [7.9 MB]
  • 10，hbase的shell操作_.mp4 [107.3 MB]
  • 4，利用python实现udf_.mp4 [13.8 MB]
  • 3，使用已有的jar包演示udf使用过程_.mp4 [47.0 MB]
  • 8，Hbase的数据模型_.mp4 [58.4 MB]
  • 6锛宧base浠嬬粛_.mp4 [38.9 MB]
  • 5锛宧ive鐨勭患鍚堟渚媉.mp4 [107.2 MB]
  • 7锛屼笂鍗堝皬缁揰.mp4 [25.7 MB]
  • 3.png [167.5 KB]
  • 思路.txt [1.3 KB]
  • 2.png [160.0 KB]
  • 1.png [86.3 KB]
资料1 条
  • 资料链接.txt [382.0 B]
视频19 集
  • 7，分布式文件系统的设计思路_.mp4 [37.5 MB]
  • 15锛宧dfs鐨勭幆澧冩惌寤篲.mp4 [74.4 MB]
  • 19，MRJob实现wordcount_.mp4 [98.2 MB]
  • 4，用户画像构建_.mp4 [67.1 MB]
  • 5，为用户推荐topN个电影_.mp4 [47.6 MB]
  • 20锛屾€荤粨_.mp4 [29.5 MB]
  • 17，MapReduce介绍及其编程流程_.mp4 [21.3 MB]
  • 8锛宧adoop鏍稿績缁勪欢_.mp4 [53.9 MB]
  • 11，hadoop的shell操作_.mp4 [28.4 MB]
  • 13，hadoop的shell操作练习_.mp4 [32.0 MB]
  • 10，hdfs的使用_.mp4 [28.5 MB]
  • 14，hdfs的架构及其优缺点_.mp4 [60.0 MB]
  • 18锛孧apReduce璁＄畻PI浣撻獙_.mp4 [24.1 MB]
  • 6锛宧adoop浠嬬粛_.mp4 [49.3 MB]
  • 12锛屼笂鍗堝皬缁揰.mp4 [26.0 MB]
  • 2，用户画像的构建_.mp4 [72.3 MB]
  • 9锛孒adoop鐨勪紭鍔縚.mp4 [3.1 MB]
  • 3锛屽€掓帓绱㈠紩_.mp4 [53.3 MB]
  • 16，YARN介绍及其YARN架构、执行流程_.mp4 [69.4 MB]
img100 条
  • 混合推荐方法.jpeg [142.4 KB]
  • 决策树.jpg [227.4 KB]
  • 并行式-加权式.jpeg [129.9 KB]
  • firststart1.png [537.2 KB]
  • algorithm4.png [101.5 KB]
  • lambda7.png [225.2 KB]
  • similarity_calc14.png [24.5 KB]
  • lambda5.png [58.1 KB]
  • user-itemMatrix.png [24.9 KB]
  • algorithm7.png [308.0 KB]
  • 用户画像2.jpg [45.0 KB]
  • userprofile1.jpeg [33.2 KB]
  • 流水线式-级联式.jpeg [122.8 KB]
  • similarity_calc3.png [78.0 KB]
  • lambda1.png [136.6 KB]
  • similarity_calc2.png [255.8 KB]
  • algorithm5.png [187.2 KB]
  • firststart.png [226.3 KB]
  • Rocchio-3.jpg [28.6 KB]
  • 流水线式混合方法.jpeg [65.4 KB]
  • lambda3.png [167.0 KB]
  • similarity_calc16.png [26.8 KB]
  • similarity_calc4.png [73.9 KB]
  • 并行式混合方法.jpeg [88.8 KB]
  • similarity_calc12.png [104.2 KB]
  • 基于物品的预测公式.jpg [22.5 KB]
  • lambda4.png [97.0 KB]
  • 并行式-切换式.jpeg [153.7 KB]
  • algorithm1(1).png [146.7 KB]
  • 整体式-特征混合.jpeg [105.2 KB]
  • od2.png [4.0 KB]
  • RS基础技术架构.png [1.1 MB]
  • algorithm6.png [238.0 KB]
  • recommend4.png [103.7 KB]
  • RS基础业务架构.png [343.2 KB]
  • recommend5.png [250.6 KB]
  • knn2.png [56.7 KB]
  • als1.png [183.0 KB]
  • algorithm2.png [146.7 KB]
  • 推荐知识库示例.jpeg [160.7 KB]
  • 整体式-特征补充.jpeg [135.1 KB]
  • 相似度计算示例.png [23.9 KB]
  • 1545049355235.png [86.6 KB]
  • Rocchio-1.jpg [18.5 KB]
  • user-itemMatrix4.png [51.1 KB]
  • similarity_calc5.png [241.9 KB]
  • knn1.png [63.8 KB]
  • 推荐流程.png [16.9 KB]
  • similarity_calc13.png [55.6 KB]
  • CF介绍.png [178.0 KB]
  • lambda2.png [199.9 KB]
  • similarity_calc6.png [56.5 KB]
  • recommend7.jpeg [13.1 KB]
  • 挖掘频繁项集.png [102.8 KB]
  • similarity_calc9.png [56.7 KB]
  • 流水线式-层叠式.jpeg [124.1 KB]
  • similarity_calc7.png [27.7 KB]
  • similarity_calc1.png [21.5 KB]
  • Rocchio-2.jpg [23.7 KB]
  • similarity_calc15.png [24.1 KB]
  • user-itemMatrix2.png [86.2 KB]
  • 基础CB推荐算法.jpg [18.2 KB]
  • 修正的余弦相似度公式.jpg [51.8 KB]
  • itemcf1.png [103.4 KB]
  • itemcf2.png [113.8 KB]
  • lambda6.png [85.4 KB]
  • 协同推荐评分数据集.jpg [65.8 KB]
  • recommend6.png [36.7 KB]
  • graph1.png [57.8 KB]
  • od.png [10.6 KB]
  • similarity_calc10.png [64.9 KB]
  • usercf3.png [4.5 KB]
  • 整体式混合方法.jpeg [103.6 KB]
  • algorithm3.png [94.8 KB]
  • firststart2.png [564.2 KB]
  • 隐因子模型介绍.jpg [158.2 KB]
  • 并行式-混杂式.jpeg [120.8 KB]
  • 基于用户的预测公式.jpg [18.6 KB]
  • similarity_calc11.png [64.4 KB]
  • user-itemMatrix3.png [37.9 KB]
  • recommend2.png [61.4 KB]
  • usercf1.png [71.8 KB]
  • usercf2.png [22.2 KB]
  • similarity_calc8.png [42.6 KB]
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  • 07_Zookeeper选举模式和伪分布式集群搭建.html [29.8 KB]
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  • 07_Zookeeper选举模式和伪分布式集群搭建.md [1.8 KB]
  • 11_storm核心概念.html [30.2 KB]
  • 03_Zookeeper基本数据模型.html [30.7 KB]
  • index.html [28.0 KB]
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code2 条
  • hbasemanager.py [1.1 KB]
  • happybase_demo.py [3.4 KB]
img51 条
  • hbase9.png [45.0 KB]
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  • README.md [253.0 B]
  • SUMMARY.md [3.3 KB]
  • 推荐系统资料备份.zip [76.5 MB]
  • 推荐系统课后作业.md [7.5 KB]
02_数据分析思路10 集
  • 09_中小公司数据分析工作介绍_.mp4 [11.1 MB]
  • 07_数据分析套路_日常工作介绍_.mp4 [17.2 MB]
  • 03_数据分析套路_漏斗分析_.mp4 [14.4 MB]
  • 08_数据分析套路_日常工作介绍2_.mp4 [43.9 MB]
  • 10_内容回顾_.mp4 [19.3 MB]
  • 04_数据分析套路_渠道分析_.mp4 [13.2 MB]
  • 02_数据分析套路_多维度分析案例_.mp4 [20.9 MB]
  • 05_数据分析套路_分布分析_.mp4 [8.0 MB]
  • 01_数据分析套路_对比分析多维度分析_.mp4 [44.3 MB]
  • 06_数据分析套路_留存分析_.mp4 [7.4 MB]
01_数据分析概要13 集
  • 12_数据指标_业务指标_.mp4 [22.3 MB]
  • 08_数据指标_日活月活_.mp4 [21.2 MB]
  • 06_数据指标_用户数据_.mp4 [43.8 MB]
  • 03_业务的概念_.mp4 [42.1 MB]
  • 02_数据分析岗位介绍_.mp4 [18.0 MB]
  • 13_数据指标_业务指标定义_.mp4 [79.0 MB]
  • 07_数据指标_行为指标业务指标_.mp4 [18.2 MB]
  • 11_数据指标_行为指标_.mp4 [21.9 MB]
  • 04_数据分析技能要求_.mp4 [24.3 MB]
  • 10_数据指标_留存指标_.mp4 [53.0 MB]
  • 01_数据科学内容概述_.mp4 [30.4 MB]
  • 09_数据指标_日活月活2_.mp4 [13.0 MB]
  • 05_数据指标概念_.mp4 [24.7 MB]
2_cms-环境搭建9 集
  • 2.3.6QQ查询数据_.mp4 [29.0 MB]
  • 2.3.3QQ增加数据_.mp4 [10.9 MB]
  • 2.3.5QQ删除数据_.mp4 [9.8 MB]
  • 2.2.2QQssi服务端包含技术_.mp4 [56.8 MB]
  • 2.3.4QQ修改数据_.mp4 [10.2 MB]
  • 2.2.3QQcms页面管理需求_.mp4 [16.2 MB]
  • 2.2.1QQ静态门户工程搭建_.mp4 [27.6 MB]
  • 2.3.2QQ瀹氫箟鏂囨。_.mp4 [44.4 MB]
  • 2.3.1QQ在django中使用MongoDB_.mp4 [22.3 MB]
11_学习中心与媒资管理39 集
  • 5.6.2QQ视频处理开发1-基础配置_.mp4 [20.7 MB]
  • 5.11.1QQ在线学习需求分析_.mp4 [5.1 MB]
  • 5.11.3QQ在线学习后端开发_.mp4 [28.6 MB]
  • 5.11.4QQ在线学习前端开发_.mp4 [65.9 MB]
  • 5.10.3QQlogstash扫描课程计划媒资_.mp4 [28.2 MB]
  • 5.7.1QQ我的媒资需求分析_.mp4 [9.4 MB]
  • 5.6.2QQ视频处理开发7-视频处理_.mp4 [88.0 MB]
  • 5.5.3.2QQ文件分块与合并2-文件分块_.mp4 [25.9 MB]
  • 5.5.1QQ媒资管理需求分析_.mp4 [19.2 MB]
  • 5.10.4QQ搜索服务查询媒资接口_.mp4 [31.7 MB]
  • 5.7.3QQ我的媒资前端开发_.mp4 [31.4 MB]
  • 5.2.1QQ视频编码格式_.mp4 [13.7 MB]
  • 5.11.2QQ搭建开发环境_.mp4 [11.5 MB]
  • 5.8.4QQ查询视频信息_.mp4 [40.4 MB]
  • 5.6.1QQ视频处理需求分析_.mp4 [11.3 MB]
  • 5.4QQ搭建学习中心前端_.mp4 [32.3 MB]
  • 5.6.2QQ视频处理开发3-VideoUtil_.mp4 [57.9 MB]
  • 5.9.1-2QQ学习页面查询课程计划需求与api接口_.mp4 [9.6 MB]
  • 5.9.4QQ学习页面查询课程计划前端开发_.mp4 [40.4 MB]
  • 5.8.2QQ选择视频2-前端实现_.mp4 [56.4 MB]
  • 5.10.2QQ课程发布存储媒资信息1-需求分析_.mp4 [7.5 MB]
  • 5.1.1QQ在线学习需求描述_.mp4 [13.1 MB]
  • 5.8.2QQ选择视频1-父子组件通信_.mp4 [15.1 MB]
  • 5.7.2QQ我的媒资服务端开发_.mp4 [34.7 MB]
  • 5.8.3QQ保存视频信息2-前端开发与测试_.mp4 [35.0 MB]
  • 5.6.2QQ视频处理开发2-视频处理技术方案_.mp4 [21.3 MB]
  • 5.5.3.1QQ断点续传解决方案_.mp4 [17.3 MB]
  • 5.6.3QQ发送视频处理消息_.mp4 [17.1 MB]
  • 5.2.3QQ生成m3u8_ts文件_.mp4 [43.6 MB]
  • 5.9.3QQ学习页面查询课程计划服务端开发_.mp4 [16.9 MB]
  • 5.8.3QQ保存视频信息1-需求分析后端实现_.mp4 [56.3 MB]
  • 5.10.2QQ课程发布存储媒资信息2-后端实现_.mp4 [50.0 MB]
  • 5.8.1QQ媒资与课程计划关联需求分析_.mp4 [11.1 MB]
  • 5.1.2QQ视频点播解决方案_.mp4 [52.8 MB]
  • 5.6.2QQ视频处理开发6-处理流程准备_.mp4 [11.4 MB]
  • 5.6.2QQ视频处理开发4-Mp4VideoUtil_.mp4 [33.2 MB]
  • 5.10.1QQ学习页面获取播放地址需求分析_.mp4 [18.2 MB]
  • 5.6.2QQ视频处理开发5-HlsVideoUtil_.mp4 [62.1 MB]
  • 5.5.3.2QQ文件分块与合并1-获取文件md5_.mp4 [21.8 MB]
8_课程管理-课程预览与发布12 集
  • 3.8.3.4QQ课程预览服务端_.mp4 [69.5 MB]
  • 3.9.3QQ课程发布接口_.mp4 [32.4 MB]
  • 3.8.2.3QQ课程信息模板设计_.mp4 [31.7 MB]
  • 3.8.2.2QQ课程数据模型查询接口_.mp4 [40.7 MB]
  • 3.8.3.2QQCMS页面预览测试_.mp4 [18.9 MB]
  • 3.9.2QQCMS一键发布接口_.mp4 [38.4 MB]
  • 3.8.2.1QQ静态页面测试_.mp4 [42.9 MB]
  • 3.9.4QQ课程发布前端开发_.mp4 [25.8 MB]
  • 3.9.1QQ课程发布需求分析_.mp4 [13.2 MB]
  • 3.8.1QQ课程预览技术方案_.mp4 [39.3 MB]
  • 3.8.3.5QQ课程预览前端_.mp4 [28.0 MB]
  • 3.8.3.3QQCMS添加页面接口_.mp4 [29.9 MB]
12_登录注册与认证授权7 集
  • 6.3QQ用户登录前端_.mp4 [67.1 MB]
  • 6.7QQ用户注册后端1-发送验证码_.mp4 [86.1 MB]
  • 6.5QQ用户退出_.mp4 [22.5 MB]
  • 6.4QQ前端显示当前用户_.mp4 [35.8 MB]
  • 6.6QQ前端集成认证授权_.mp4 [49.4 MB]
  • 6.8QQ用户注册前端_.mp4 [31.9 MB]
  • 6.7QQ用户注册后端1-用户注册_.mp4 [61.4 MB]
3_cms-页面管理后端9 集
  • 2.4.2.2QQ封装异常处理_.mp4 [74.1 MB]
  • 2.4.7QQ椤甸潰璇︽儏_.mp4 [18.8 MB]
  • 2.4.2.3QQ灏佽JSON杩斿洖鍊糭.mp4 [40.1 MB]
  • 2.4.6.3QQ自定义条件查询_.mp4 [32.5 MB]
  • 2.4.4QQ站点列表和模板列表_.mp4 [41.7 MB]
  • 2.4.9QQ鍒犻櫎椤甸潰_.mp4 [21.7 MB]
  • 2.4.2.1QQ接口开发规范_.mp4 [16.2 MB]
  • 2.4.1QQ使用MongoEngine定义接口_.mp4 [40.6 MB]
  • 2.4.3QQ数据模型定义_.mp4 [22.7 MB]
5_cms-课程静态化及预览发布13 集
  • 2.6.4.3QQ页面发布消费方_.mp4 [61.4 MB]
  • 2.6.1QQ页面静态化需求_.mp4 [12.2 MB]
  • 2.6.2.3.1QQ模板管理业务流程_.mp4 [9.1 MB]
  • 2.6.2.2QQ数据模型_.mp4 [58.3 MB]
  • 2.6.2.3.5-1QQ闈欐€佸寲绋嬪簭_.mp4 [67.7 MB]
  • 2.6.2.3.4QQ模板存储_.mp4 [28.6 MB]
  • 2.6.2.1QQ页面静态化流程_.mp4 [20.7 MB]
  • 2.6.2.3.2QQ妯℃澘鍒朵綔_.mp4 [52.5 MB]
  • 2.6.3.2QQ页面预览测试_.mp4 [28.7 MB]
  • 2.6.4.4QQ页面发布生产方_.mp4 [49.6 MB]
  • 2.6.3.1QQ页面预览开发_.mp4 [30.5 MB]
  • 2.6.2.3.5-2QQ静态化程序测试_.mp4 [23.6 MB]
  • 2.6.4.5QQ页面发布前端实现_.mp4 [24.3 MB]
7_课程管理-课程计划及课程图片21 集
  • 3.7.4.3QQ图片删除前端_.mp4 [38.9 MB]
  • 3.7.1.4QQ上传图片前端_.mp4 [39.5 MB]
  • 3.6.1QQ课程计划需求分析_.mp4 [12.1 MB]
  • 3.6.2.1QQ课程计划查询功能分析_.mp4 [7.5 MB]
  • 3.7.2.1QQ保存课程图片需求分析_.mp4 [7.9 MB]
  • 3.7.2.2QQ保存图片服务端_.mp4 [34.3 MB]
  • 3.7.1.2QQ文件系统服务环境搭建_.mp4 [19.8 MB]
  • 3.7.2.3QQ保存图片前端_.mp4 [32.3 MB]
  • 3.7.3.3QQ图片查询前端_.mp4 [25.6 MB]
  • 3.6.3.3QQ添加课程计划服务端_.mp4 [25.9 MB]
  • 3.6.3.2QQ添加课程计划页面原型_.mp4 [35.7 MB]
  • 3.6.2.3QQ课程计划服务端_.mp4 [59.8 MB]
  • 3.6.2.4QQ课程计划前端页面_.mp4 [43.9 MB]
  • 3.6.3.4QQ添加课程计划前端_.mp4 [25.5 MB]
  • 3.7.1.3QQ上传图片服务端_.mp4 [74.4 MB]
  • 3.6.2.2QQ课程计划页面原型_.mp4 [35.9 MB]
  • 3.7.3.1-2QQ图片查询需求分析与服务端_.mp4 [12.3 MB]
  • 3.7.4.2QQ图片删除服务端_.mp4 [19.4 MB]
  • 3.6.3.1QQ添加课程计划需求分析_.mp4 [9.2 MB]
  • 3.7.4.1QQ图片删除需求分析_.mp4 [8.8 MB]
  • 3.7.1.1QQ上传图片需求分析_.mp4 [19.1 MB]
6_课程管理-我的课程基本信息及营销信息18 集
  • 3.2.3QQ我的课程前端1-页面布局_.mp4 [33.3 MB]
  • 3.3.2QQ课程分类查询_.mp4 [77.4 MB]
  • 3.5.3QQ课程营销信息服务端_.mp4 [39.7 MB]
  • 3.4.1QQ课程信息修改需求分析_.mp4 [7.2 MB]
  • 3.3.4QQ新增课程页面内容完善_.mp4 [56.5 MB]
  • 3.4.3QQ课程修改服务端_.mp4 [14.0 MB]
  • 3.3.6QQ新增课程前端_.mp4 [29.4 MB]
  • 3.2.2QQ我的课程后端_.mp4 [23.4 MB]
  • 3.5.2QQ课程营销数据模型_.mp4 [4.3 MB]
  • 3.2.3QQ我的课程前端2-api及测试_.mp4 [27.5 MB]
  • 3.3.5QQ创建课程服务端_.mp4 [8.7 MB]
  • 3.5.1QQ课程营销需求分析_.mp4 [9.7 MB]
  • 3.4.2QQ课程管理页面说明_.mp4 [70.8 MB]
  • 3.2.1QQ我的课程需求分析_.mp4 [9.8 MB]
  • 3.5.4QQ课程营销前端_.mp4 [39.4 MB]
  • 3.3.1QQ创建课程需求分析_.mp4 [6.2 MB]
  • 3.3.3QQ数据字典_.mp4 [60.0 MB]
  • 3.4.4QQ课程修改前端_.mp4 [51.8 MB]
9_课程搜索-搜索后端11 条
  • 4.3.3QQ定义ESClient3-ESClient实现及测试_.pcwlenv [66.0 MB]
  • 4.3.2QQ创建搜索应用_.pcwlenv [20.0 MB]
  • 4.3.3QQ定义ESClient1-代码讲解_.pcwlenv [50.3 MB]
  • 4.3.4QQ课程搜索服务端开发_.pcwlenv [29.2 MB]
  • 4.1QQ课程搜索需求分析_.pcwlenv [20.0 MB]
  • 4.2.3QQ搭建ES环境_.pcwlenv [29.9 MB]
  • 4.2.4QQLogstash创建索引_.pcwlenv [116.0 MB]
  • 4.2.1QQ课程索引技术方案_.pcwlenv [13.4 MB]
  • 4.3.1QQ课程搜索功能需求_.pcwlenv [12.7 MB]
  • 4.3.3QQ定义ESClient2-BaseESClient实现_.pcwlenv [66.9 MB]
  • 4.2.2QQ准备课程索引信息_.pcwlenv [131.7 MB]
13_订单与选课12 集
  • 7.5.2QQ订单服务定时发送消息-查询前N条任务_.mp4 [37.5 MB]
  • 7.3.2QQ自动添加选课方案-解决方案_.mp4 [16.5 MB]
  • 7.6.4QQ自动添加选课-集成测试_.mp4 [13.8 MB]
  • 7.1QQ订单与选课需求分析_.mp4 [26.4 MB]
  • 7.4QQCeleryQQBeat定时任务_.mp4 [51.1 MB]
  • 7.6.2QQ自动添加选课-学习服务添加选课_.mp4 [36.5 MB]
  • 7.5.1QQ订单服务定时发送消息-需求分析_.mp4 [7.2 MB]
  • 7.2.2QQ什么是分布式事务_.mp4 [25.8 MB]
  • 7.2.4QQ分布式事务解决方案_.mp4 [44.8 MB]
  • 7.3.1QQ自动添加选课方案-环境搭建_.mp4 [28.5 MB]
  • 7.6.1QQ自动添加选课-RabbitMQ配置_.mp4 [22.0 MB]
  • 7.6.3QQ自动添加选课-订单服务结束任务_.mp4 [19.9 MB]
10_课程搜索-搜索前端8 集
  • 4.7QQ闆嗘垚娴嬭瘯_.mp4 [11.5 MB]
  • 4.5.3QQ椤甸潰甯冨眬_.mp4 [12.7 MB]
  • 4.5.4QQ路由_.mp4 [32.4 MB]
  • 4.6.5QQ按难度等级搜索_.mp4 [12.5 MB]
  • 4.6.4QQ鎸夊垎绫绘悳绱.mp4 [56.1 MB]
  • 4.6.1QQ鎼滅储椤甸潰_.mp4 [43.4 MB]
  • 4.5.5QQ获取数据_.mp4 [48.1 MB]
  • 4.4.2QQ服务端渲染和客户端渲染_.mp4 [28.9 MB]
1_项目概述3 集
  • 1.2QQ项目的功能架构_.mp4 [25.8 MB]
  • 1.3QQ项目的技术架构_.mp4 [24.5 MB]
  • 1.1QQ传智云课堂项目背景_.mp4 [11.8 MB]
4_cms-页面管理前端14 集
  • 2.5.3.2-3QQapi调用-添加页面测试_.mp4 [24.1 MB]
  • 2.5.2.5QQ进入页面立即查询_.mp4 [15.7 MB]
  • 2.5.4.1-2QQ页面处理流程QQ修改页面_.mp4 [44.6 MB]
  • 2.5.2.1.3QQ页面内容完善_.mp4 [41.7 MB]
  • 2.5.2.6QQ自定义条件查询_.mp4 [52.9 MB]
  • 2.5.2.1.1QQ鍒涘缓椤甸潰_.mp4 [32.5 MB]
  • 2.5.2.3QQ跨域问题解决_.mp4 [40.0 MB]
  • 2.5.3.1QQ新增页面2-页面完善_.mp4 [49.7 MB]
  • 2.5.2.4QQ分页查询测试_.mp4 [18.1 MB]
  • 2.5.5QQ删除页面前端开发_.mp4 [23.9 MB]
  • 2.5.2.1.2QQTable缁勪欢娴嬭瘯_.mp4 [30.9 MB]
  • 2.5.1.1QQ导入系统管理前端工程_.mp4 [27.6 MB]
  • 2.5.2.7QQ前后端请求响应小结_.mp4 [16.7 MB]
  • 2.5.1.2QQ单页面应用介绍_.mp4 [20.4 MB]
资料16 条
  • 12阶段：WEB方向进价【选修】.exe [66.2 MB]
  • 01_基础班.exe [366.6 MB]
  • python安装包.exe [5.2 GB]
  • 13阶段：运维开发方向【选修】.exe [268.0 MB]
  • 06阶段：数据采集.exe [43.7 MB]
  • 07阶段：Web-Flask框架与项目.exe [4.1 GB]
  • 应用安装包.exe [1.4 GB]
  • 08阶段：数据分析课程.exe [7.3 GB]
  • 02阶段：python高级.exe [103.6 MB]
  • 03阶段：Django框架与项目.exe [148.8 MB]
  • 04阶段：项目部署和管理.exe [1.2 GB]
  • 10阶段：云课堂.exe [1.5 GB]
  • 11阶段：爬虫进价方向【选修】.exe [194.0 MB]
  • 14阶段：深度学习进价方向【选修】.exe [2.9 GB]
  • 09阶段：黑马文学.exe [69.4 MB]
  • 05阶段：项目测试和监控.exe [233.8 MB]
_idea2 条
  • data [29.0 B]
  • text [2.0 KB]
_idea1 条
  • Day05.iml [408.0 B]
_idea1 条
  • Day10.iml [408.0 B]
_idea1 条
  • Day08.iml [408.0 B]
_idea2 条
  • Day04.iml [408.0 B]
  • Day04(1).iml [408.0 B]
_idea1 条
  • Day09.iml [408.0 B]
_idea1 条
  • Day06.iml [408.0 B]
_idea1 条
  • Day07.iml [408.0 B]
_idea2 条
  • Day03(1).iml [398.0 B]
  • Day03.iml [398.0 B]
_idea2 条
  • Day02.iml [408.0 B]
  • Day02(1).iml [408.0 B]

适合人群

  • Python初学者
  • 人工智能爱好者
  • 爬虫开发者

🎯 学习收获

  • 掌握Python 6.0基础
  • 精通爬虫技术
  • 学会人工智能应用

🎉 祝您学习愉快！

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