知乎大模型15期|2025完结

课程目录

├──0-AI大模型第15期正课【视频课文件夹】
| ├──10. MCP与A2A的应用.mp4 418.68M
| ├──11. Agent智能体系统的设计与应用.mp4 395.90M
| ├──12. 视觉大模型与多模态理解.mp4 407.50M
| ├──13. Fine-tuning 微调艺术.mp4 313.89M
| ├──14. Fine-tuning 实操.mp4 405.44M
| ├──15. Coze工作原理与应用实例.mp4 363.31M
| ├──16. Coze插件开发实战.mp4 363.64M
| ├──17. Dify本地化部署和应用.mp4 377.14M
| ├──18. 分析式AI基础.mp4 354.30M
| ├──19. 不同领域的AI算法.mp4 352.16M
| ├──1、AI大模型基本原理及API应用.mp4 367.00M
| ├──20. 机器学习神器.mp4 317.21M
| ├──21. 时间序列模型.mp4 350.69M
| ├──22. 时间序列大赛.mp4 410.70M
| ├──23. 神经网络基础与Tensorflow实战.mp4 347.59M
| ├──24. Pytorch与视觉检测.mp4 382.13M
| ├──25. 项目实战：企业知识库 （企业RAG大赛冠军项目）.mp4 486.81M
| ├──26. 项目实战：交互式BI报表 （AI量化交易助手）.mp4 483.49M
| ├──27. 项目实战：AI智慧运营助手（百万客群经营）.mp4 493.46M
| ├──28. 项目实战：AI搜索类应用 （知乎直答）.mp4 570.67M
| ├──2、DeepSeek使用与prompt工程.mp4 333.99M
| ├──3、Cursor编程-从入门到精通.mp4 396.43M
| ├──4、Embeddings和向量数据库.mp4 351.70M
| ├──5、RAG技术与应用.mp4 380.17M
| ├──6.RAG的高级技巧.mp4 380.17M
| ├──6、RAG的高级技巧.mp4 389.58M
| ├──7. Text2SQL：自助式数据报表开发.mp4 389.58M
| ├──8. LangChain：多任务应用开发.mp4 414.36M
| └──9. Function Calling与智能Agent开发.mp4 380.39M
├──1-AI大模型原理与API使用
| ├──CASE-API使用
| | ├──.cursorindexingignore 0.11kb
| | ├──1-情感分析-Qwen.ipynb 1.82kb
| | ├──1-情感分析-Qwen.py 0.86kb
| | ├──2-天气Function-Qwen.ipynb 7.43kb
| | ├──2-天气Function-Qwen.py 3.55kb
| | ├──3-表格提取-Qwen.ipynb 5.34kb
| | ├──3-表格提取-Qwen.py 0.84kb
| | ├──4-运维事件处置-Qwen.ipynb 6.79kb
| | ├──4-运维事件处置-Qwen.py 3.31kb
| | ├──5-情感分析-Deepseek-阿里代理.ipynb 1.79kb
| | ├──5-情感分析-Deepseek-阿里代理.py 0.77kb
| | ├──6-联网搜索.ipynb 2.36kb
| | └──6-联网搜索.py 0.88kb
| ├──1-AI大模型原理与API使用.pdf 3.15M
| ├──笔记20250721.txt 0.52kb
| └──课前注册API KEY.txt 0.20kb
├──10-MCP与A2A的应用
| ├──CASE-A2A使用
| | ├──BasketBallAgent.py 2.01kb
| | ├──requirements.txt 0.07kb
| | └──WeatherAgent.py 1.79kb
| ├──CASE-MCP Demo-1
| | ├──.specstory
| | ├──.cursorindexingignore 0.11kb
| | ├──.gitignore 0.01kb
| | ├──assistant_mcp_amap_bot.py 6.30kb
| | ├──assistant_mcp_txt_bot.py 6.21kb
| | ├──requirements.txt 0.05kb
| | ├──txt_counter.py 2.02kb
| | └──旅行规划.md 4.60kb
| ├──CASE-MCP Demo-2
| | ├──.specstory
| | ├──.cursorindexingignore 0.11kb
| | ├──assistant_bot.py 6.21kb
| | └──requirements.txt 0.04kb
| ├──1-MCP与A2A的应用.pdf 5.69M
| └──笔记20250820.txt 5.82kb
├──11-Agent智能体系统的设计与应用
| ├──CASE-私募基金运作指引问答助手（反应式）
| | └──fund_qa_langgraph.py 13.80kb
| ├──CASE-投顾AI助手（混合式）
| | └──hybrid_wealth_advisor_langgraph.py 22.90kb
| ├──CASE-智能投研助手（深思熟虑）
| | └──deliberative_research_langgraph.py 18.42kb
| ├──1-Agent智能体系统的设计与应用.pdf 2.79M
| └──笔记20250823.txt 6.58kb
├──12-视觉大模型与多模态理解
| ├──CASE-MinerU使用
| | ├──.ipynb_checkpoints
| | ├──modelscope_models
| | ├──output
| | ├──temp
| | ├──1-MinerU.ipynb 3.06kb
| | ├──download_models.py 2.44kb
| | ├──download_models_hf.py 2.40kb
| | ├──markdown.md 51.77kb
| | ├──Qwen3-tech_report.pdf 6.09M
| | └──三国演义.pdf 3.75M
| ├──CASE-VLM在车险中的应用
| | ├──.ipynb_checkpoints
| | ├──1-Qwen-VL-保险识别-cn.ipynb 23.78kb
| | ├──1-vehicle-odometer-reading.jpg 22.40kb
| | ├──10-extraction-of-auto-accident-elements.jpg 120.51kb
| | ├──11-vehicle-identity-verification-1.jpg 47.79kb
| | ├──11-vehicle-identity-verification-2.jpg 51.02kb
| | ├──12-vehicle-identity-verification-1.jpg 60.98kb
| | ├──12-vehicle-identity-verification-2.jpg 81.03kb
| | ├──2-Qwen-VL-chat1.ipynb 865.74kb
| | ├──2-vehicle-odometer-reading.jpg 86.14kb
| | ├──3-vehicle-underwriting-1.jpg 38.94kb
| | ├──3-vehicle-underwriting-2.jpg 44.99kb
| | ├──3-vehicle-underwriting-3.jpg 46.13kb
| | ├──3-vehicle-underwriting-4.jpg 41.67kb
| | ├──3-vehicle-underwriting-5.jpg 32.84kb
| | ├──4-Dangerous-driving-behavior-detection.jpg 43.33kb
| | ├──5-Dangerous-driving-behavior-detection.jpg 29.72kb
| | ├──6-Dangerous-driving-behavior-detection-1.jpg 19.83kb
| | ├──6-Dangerous-driving-behavior-detection-2.jpg 20.10kb
| | ├──6-Dangerous-driving-behavior-detection-3.jpg 19.42kb
| | ├──6-Dangerous-driving-behavior-detection-4.jpg 21.20kb
| | ├──6-Dangerous-driving-behavior-detection-5.jpg 23.60kb
| | ├──7-vehicle-damage-evaluation.jpg 68.60kb
| | ├──8-vehicle-damage-evaluation.jpg 42.22kb
| | ├──9-extraction-of-auto-accident-elements.jpg 74.18kb
| | ├──prompt_template_cn.xlsx 9.87kb
| | ├──prompt_template_cn_result-20250430.xlsx 17.67kb
| | ├──prompt_template_cn_result.xlsx 13.54kb
| | ├──prompt_template_en.xlsx 9.73kb
| | └──prompt_template_en_result.xlsx 9.79kb
| ├──CASE-VLM在寿险中的应用
| | ├──.ipynb_checkpoints
| | ├──1-Chinese-document-extraction.jpg 80.99kb
| | ├──1-Qwen-VL-保险识别-cn.ipynb 11.01kb
| | ├──2-Japanese-document-extraction.jpg 173.05kb
| | ├──2-Qwen-VL-本地图片.ipynb 4.08kb
| | ├──3-French-document-extraction.jpg 202.74kb
| | ├──4-German-document-extraction.jpg 142.75kb
| | ├──5-Korean-document-extraction.jpg 117.13kb
| | ├──prompt_template_cn.xlsx 9.10kb
| | └──prompt_template_cn_result.xlsx 7.88kb
| ├──CASE-汽车剐蹭视频理解
| | ├──car.mp4 5.77M
| | ├──requirements.txt 0.10kb
| | ├──video-understand.ipynb 18.61kb
| | └──video-understand.py 9.71kb
| ├──笔记20250827.txt 2.76kb
| └──视觉大模型与多模态理解.pdf 6.66M
├──13-Fine-tuning微调艺术
| ├──image_svd
| | ├──256.bmp 1.48M
| | └──image_svd.py 0.88kb
| ├──MovieLens
| | ├──ALS.py 14.63kb
| | ├──ratings_small.csv 2.33M
| | └──ratings_small2.csv 2.13M
| ├──1-Fine-tuning微调艺术.pdf 1.31M
| └──笔记20250830.txt 2.89kb
├──14-Fine-tuning实操
| ├──images
| | ├──1-vehicle-odometer-reading.jpg 22.40kb
| | └──2-vehicle-odometer-reading.jpg 86.14kb
| ├──【数据集】alpaca-cleaned
| | ├──alpaca_data_cleaned.json 42.25M
| | ├──gitattributes 2.27kb
| | └──README.md 11.34kb
| ├──【数据集】gsm8k
| | ├──main
| | ├──socratic
| | ├──gitattributes 1.57kb
| | ├──gsm8k.zip 4.89M
| | └──README.md 7.75kb
| ├──【数据集】中文医疗数据
| | ├──Andriatria_男科
| | ├──IM_内科
| | ├──OAGD_妇产科
| | ├──Oncology_肿瘤科
| | ├──Pediatric_儿科
| | └──Surgical_外科
| ├──1-Fine-tuning实操.pdf 2.59M
| ├──qwen-vl-train.xlsx 9.89kb
| ├──Qwen2_5_(7B)_Alpaca-2.ipynb 169.72kb
| ├──Qwen2_5_(7B)_Alpaca-2.py 12.53kb
| ├──Qwen2_5_(7B)_R1.ipynb 528.96kb
| ├──Qwen2_5_(7B)_R1.py 8.67kb
| ├──Qwen2_5_(7B)_模型调用.ipynb 53.01kb
| ├──Qwen2_5_(7B)_医疗微调.ipynb 685.16kb
| ├──Qwen2_5_(7B)_医疗微调.py 11.46kb
| ├──qwen_vl_car_insurance_train.ipynb 37.59kb
| ├──qwen_vl_car_insurance_train.py 8.33kb
| ├──requirements.txt 0.23kb
| └──笔记20250903.txt 2.82kb
├──15-Coze工作原理与应用实例
| ├──CASE：创建产品知识库
| | ├──大模型定价.xlsx 8.75kb
| | ├──浦发上海浦东发展银行西安分行个金客户经理考核办法.pdf 368.62kb
| | └──远程办公场景最佳实践.docx 469.57kb
| └──1-Coze工作原理与应用实例.pdf 5.83M
├──15-Coze工作原理与应用实例(1)
| ├──CASE：创建产品知识库
| | ├──大模型定价.xlsx 8.75kb
| | ├──浦发上海浦东发展银行西安分行个金客户经理考核办法.pdf 368.62kb
| | └──远程办公场景最佳实践.docx 469.57kb
| ├──1-Coze工作原理与应用实例.pdf 5.96M
| └──笔记20250906.txt 2.08kb
├──16-Agent进阶实战与插件开发
| ├──CASE-客户分层营销助手
| | ├──user_behavior_event.xlsx 9.96kb
| | ├──user_tag.xlsx 9.19kb
| | └──营销策略.xlsx 12.64kb
| ├──CASE-市场舆情监测Agent
| | ├──AppStorePast-代码1.py 0.48kb
| | ├──AppStorePast.py 1.05kb
| | ├──securities_past.py 2.58kb
| | ├──代码.js 1.22kb
| | └──代码1.py 0.34kb
| ├──CASE-智能客服Agent
| | ├──user_complain.xlsx 8.92kb
| | ├──港股交易规则介绍.pdf 954.16kb
| | ├──平安财富日添利理财产品.doc 30.00kb
| | ├──上海证券交易所交易规则.pdf 378.09kb
| | └──中国平安金裕人生理财产品.doc 61.00kb
| ├──ABC公司证券产品介绍.txt 6.66kb
| ├──Agent进阶实战与插件开发.pdf 6.41M
| ├──Workflow-AppStoreEstimate-draft-4824.zip 5.60kb
| ├──Workflow-GenerateDailyReports-draft-4867.zip 4.26kb
| ├──Workflow-Securities-draft-5188.zip 6.45kb
| └──笔记20250910.txt 5.73kb
├──17-Dify本地化部署和应用
| ├──CASE-Coze API使用
| | ├──__pycache__
| | ├──config.py 0.40kb
| | ├──coze_client.py 9.10kb
| | └──requirements.txt 0.04kb
| ├──CASE-Dify API使用
| | ├──__pycache__
| | ├──dify_agent_client.py 19.92kb
| | ├──dify_workflow_example.py 0.93kb
| | └──requirements.txt 0.04kb
| ├──CASE-智能客服ChatFlow
| | ├──user_behavior_event.xlsx 9.96kb
| | ├──user_tag.xlsx 9.19kb
| | ├──港股交易规则介绍.pdf 954.16kb
| | ├──平安财富日添利理财产品.doc 30.00kb
| | ├──上海证券交易所交易规则.pdf 378.09kb
| | └──中国平安金裕人生理财产品.doc 61.00kb
| ├──CASE-智能文档分析助手
| | └──INTERNVIDEO2.5.pdf 1.84M
| ├──1-Dify部署与应用.pdf 4.18M
| └──笔记20250913.txt 8.84kb
├──18-分析式AI基础
| ├──Case-二手车价格预测
| | ├──used_car_sample_submit.csv 439.47kb
| | ├──used_car_testB_20200421.csv 17.06M
| | └──used_car_train_20200313.csv 51.77M
| ├──【完成参考】Case-二手车价格预测
| | ├──catboost_info
| | ├──processed_data
| | ├──temp
| | ├──.gitignore 0.01kb
| | ├──brand_distribution.png 19.15kb
| | ├──catboost_feature_importance.csv 0.98kb
| | ├──catboost_feature_importance.png 28.69kb
| | ├──catboost_prediction_vs_actual.png 79.54kb
| | ├──catboost_submit_result.csv 1.26M
| | ├──correlation_heatmap.png 454.95kb
| | ├──data_preprocessing.py 8.03kb
| | ├──ensemble_analysis.png 74.16kb
| | ├──feature_engineering_and_catboost.py 14.02kb
| | ├──feature_importance.csv 0.85kb
| | ├──feature_importance.png 28.14kb
| | ├──fe_catboost_feature_importance.csv 2.25kb
| | ├──fe_catboost_feature_importance.png 36.91kb
| | ├──fe_catboost_prediction_vs_actual.png 80.20kb
| | ├──fe_catboost_submit_result.csv 1.26M
| | ├──lightgbm_feature_importance.png 29.07kb
| | ├──lightgbm_prediction_vs_actual.png 80.01kb
| | ├──lightgbm_submit_result.csv 1.26M
| | ├──model_ensemble.py 3.74kb
| | ├──prediction_vs_actual.png 78.76kb
| | ├──predict_catboost.py 6.14kb
| | ├──price_distribution.png 17.99kb
| | ├──price_vs_kilometer.png 72.02kb
| | ├──price_vs_power.png 47.34kb
| | ├──price_vs_v_0.png 112.22kb
| | ├──price_vs_v_1.png 140.78kb
| | ├──price_vs_v_2.png 83.39kb
| | ├──submit_result-xgboost.csv 861.07kb
| | ├──submit_result.csv 1.26M
| | ├──train_catboost.py 4.99kb
| | ├──train_lightgbm.py 5.31kb
| | ├──train_xgboost.py 4.65kb
| | ├──used_car_sample_submit.csv 439.47kb
| | ├──used_car_testB_20200421.csv 17.06M
| | ├──used_car_train_20200313.csv 51.77M
| | ├──view_data.py 4.29kb
| | └──特征工程.md 3.51kb
| ├──1-分析式AI基础.pdf 2.43M
| └──笔记20250917.txt 4.87kb
├──19-不同领域的AI算法
| ├──【完成参考】Case-二手车价格预测
| | ├──.ipynb_checkpoints
| | ├──.specstory
| | ├──catboost_info
| | ├──processed_data
| | ├──.cursorindexingignore 0.11kb
| | ├──catboost_pred.py 1.21kb
| | ├──catboost_submit_result.csv 1.26M
| | ├──eda_used_car.ipynb 13.39kb
| | ├──eda_used_car.py 2.56kb
| | ├──ensemble_submit.py 0.97kb
| | ├──feature_engineering_and_catboost.ipynb 104.33kb
| | ├──feature_engineering_and_catboost.md 5.60kb
| | ├──feature_engineering_and_catboost.py 13.44kb
| | ├──fe_catboost_feature_importance.csv 1.87kb
| | ├──fe_catboost_feature_importance.png 34.75kb
| | ├──fe_catboost_prediction_vs_actual.png 70.12kb
| | ├──fe_catboost_submit_result.csv 1.26M
| | ├──pickle_save.py 1.58kb
| | ├──used_car_sample_submit.csv 439.47kb
| | ├──used_car_testB_20200421.csv 17.06M
| | ├──used_car_train_20200313.csv 51.77M
| | └──xgboost_pred.py 2.66kb
| ├──1-不同领域的AI算法.pdf 3.09M
| └──笔记20250920.txt 5.58kb
├──2-DeepSeek使用与Prompt工程
| ├──ball
| | └──index.html 6.35kb
| ├──1-DeepSeek使用与提示词工程.pdf 4.43M
| ├──1-情感分析-Deepseek-阿里代理.ipynb 2.34kb
| ├──1-情感分析-Deepseek-阿里代理.py 1.08kb
| ├──2-提示词工程使用.ipynb 11.84kb
| ├──2-提示词工程使用.py 3.70kb
| ├──3-deepseek-r1-7b使用.ipynb 6.62kb
| ├──3-deepseek-r1-7b使用.py 0.97kb
| ├──4-model-download.ipynb 0.78kb
| ├──5-ollama使用.py 0.55kb
| ├──6-ollama-stream.py 1.54kb
| ├──7-ollama-fastapi-python客户端.py 0.16kb
| ├──7-ollama-fastapi.py 0.97kb
| ├──requirements.txt 0.04kb
| └──笔记20250724.txt 5.00kb
├──20-机器学习神器
| ├──Attrition
| | ├──catboost_info
| | ├──attrition.csv 183.15kb
| | ├──attrition_cart.py 2.98kb
| | ├──attrition_catboost.py 2.25kb
| | ├──attrition_gbdt.py 1.57kb
| | ├──attrition_lgb.py 2.76kb
| | ├──attrition_lgb_onehot.py 2.23kb
| | ├──attrition_lr.py 3.10kb
| | ├──attrition_lr_threshold.py 2.32kb
| | ├──attrition_ngboost.py 1.64kb
| | ├──attrition_svc.py 2.74kb
| | ├──attrition_xgboost.py 2.12kb
| | ├──submit_cb.csv 2.10kb
| | ├──submit_gbdt.csv 7.29kb
| | ├──submit_lgb.csv 2.10kb
| | ├──submit_lr.csv 7.18kb
| | ├──submit_lr_threshold.csv 2.10kb
| | ├──submit_ngb.csv 2.10kb
| | ├──submit_svc.csv 2.10kb
| | ├──submit_xgb.csv 4.62kb
| | ├──test.csv 45.18kb
| | ├──train.csv 183.15kb
| | └──train_label_encoder.csv 97.84kb
| ├──voice
| | ├──voice.csv 1.02M
| | ├──voice_predict.ipynb 107.84kb
| | └──voice_predict.py 2.90kb
| ├──1-机器学习神器.pdf 1.74M
| └──笔记20250924.txt 4.18kb
├──21-时间序列模型
| ├──CASE-资金流入流出预测
| | ├──comp_predict_table.csv 0.08kb
| | ├──mfd_bank_shibor.csv 19.06kb
| | ├──mfd_day_share_interest.csv 9.53kb
| | ├──user_balance_table.csv 150.45M
| | └──user_profile_table.csv 728.55kb
| ├──sales_prediction
| | ├──.ipynb_checkpoints
| | ├──predict1.ipynb 37.35kb
| | ├──sales.csv 0.64kb
| | └──sales_prediction.py 2.99kb
| ├──stock
| | ├──1-stock_tsa.ipynb 87.40kb
| | ├──1-stock_tsa.py 0.73kb
| | ├──2-arma-demo.ipynb 179.94kb
| | ├──2-arma_demo.py 1.36kb
| | ├──3-stock_arma.ipynb 289.04kb
| | ├──4-stock_arima.ipynb 164.45kb
| | ├──4-stock_arima.py 2.99kb
| | ├──5-stock_prophet.ipynb 160.24kb
| | ├──688692_SH_close_price.png 58.81kb
| | ├──688692_SH_daily_data.csv 16.93kb
| | ├──688692_SH_full_prediction.png 69.79kb
| | ├──688692_SH_model_fit_seasonal.png 100.82kb
| | ├──688692_SH_prediction_seasonal.png 56.80kb
| | ├──688692_SH_prediction_seasonal_results.csv 0.59kb
| | ├──download_688692SH.py 2.44kb
| | ├──download_688692SH_alt.py 3.70kb
| | ├──predict_688692SH.py 5.90kb
| | ├──predict_688692SH_prophet.py 6.22kb
| | ├──predict_688692SH_seasonal.py 6.78kb
| | ├──README.md 2.20kb
| | ├──run_all_predictions.py 7.66kb
| | ├──shanghai_index_1990_12_19_to_2020_03_12.csv 270.06kb
| | ├──stock_arima.py 3.08kb
| | ├──stock_arma.py 3.16kb
| | ├──stock_lstm.py 4.25kb
| | ├──stock_prophet.py 1.06kb
| | └──stock_tsa.py 0.65kb
| ├──1-时间序列分析.pdf 1.96M
| └──笔记20250927.txt 6.15kb
├──22-时间序列AI大赛
| ├──CASE-资金流入流出预测
| | ├──.specstory
| | ├──comp_predict_table.csv 0.08kb
| | ├──mfd_bank_shibor.csv 19.06kb
| | ├──mfd_day_share_interest.csv 9.53kb
| | ├──periodic_factor_decompose_forecast_201409.csv 1.09kb
| | ├──periodic_factor_decompose_predict.py 3.26kb
| | ├──periodic_factor_forecast_201409.csv 1.06kb
| | ├──periodic_factor_predict.py 2.17kb
| | ├──periodic_forecast_201409.csv 1.06kb
| | ├──periodic_model.py 2.79kb
| | ├──periodic_model_explanation.md 2.64kb
| | ├──predict.py 3.59kb
| | ├──user_balance_table.csv 150.45M
| | ├──user_profile_table.csv 728.55kb
| | └──weekday_analysis.py 2.87kb
| ├──jetrail
| | ├──.specstory
| | ├──daily_passenger_forecast.png 146.16kb
| | ├──daily_passenger_forecast.py 2.49kb
| | ├──daily_passenger_forecast_components.png 87.79kb
| | ├──manning_prophet.py 3.44kb
| | ├──read_data.py 0.11kb
| | └──train.csv 477.59kb
| ├──manning
| | ├──.ipynb_checkpoints
| | ├──manning.csv 84.81kb
| | ├──manning_prophet.ipynb 1.18M
| | ├──manning_prophet.py 3.44kb
| | ├──突变点检测.ipynb 165.16kb
| | └──突变点检测.py 1.93kb
| ├──stock
| | ├──.ipynb_checkpoints
| | ├──.specstory
| | ├──.cursorindexingignore 0.11kb
| | ├──arma_demo.py 1.26kb
| | ├──shanghai_index_1990_12_19_to_2020_03_12.csv 270.06kb
| | ├──stock_arima.py 3.08kb
| | ├──stock_arma.py 3.16kb
| | ├──stock_lstm.py 4.25kb
| | ├──stock_prophet.ipynb 243.75kb
| | ├──stock_prophet.py 1.01kb
| | └──stock_tsa.py 0.65kb
| ├──笔记20250928.txt 4.04kb
| └──时间序列AI大赛.pdf 1.61M
├──23-神经网络基础与Tensorflow实战
| ├──code
| | ├──activation_function
| | ├──housing.csv 47.93kb
| | ├──numpy_boston.py 2.28kb
| | ├──numpy_forward.py 1.18kb
| | ├──numpy_model.py 2.38kb
| | ├──pytorch_boston.py 2.02kb
| | ├──tensorflow_boston.py 1.69kb
| | └──tensorflow_boston_dataparallel.py 1.89kb
| ├──1-神经网络基础与Tensorflow实战.pdf 1.73M
| └──笔记20251004.txt 1.91kb
├──24-pytorch与视觉检测
| ├──aistudio-baidu代码
| | ├──2531163.ipynb 72.90kb
| | └──bug_detect.tar 106.14M
| ├──CNN_cases
| | ├──.ipynb_checkpoints
| | ├──image_recognition
| | ├──cifar10_resnet.py 2.99kb
| | ├──cnn_feature_map_demo.ipynb 1.70kb
| | ├──cnn_feature_map_demo.py 0.70kb
| | ├──cnn_viz.ipynb 1.59M
| | ├──cnn_viz.py 3.33kb
| | ├──gugong.jpg 35.72kb
| | ├──mat_read.py 0.89kb
| | ├──mnist_alexnet.py 4.81kb
| | └──stanford_car_resnet.py 3.58kb
| ├──labelImg-master
| | ├──build-tools
| | ├──data
| | ├──demo
| | ├──libs
| | ├──requirements
| | ├──resources
| | ├──tests
| | ├──__pycache__
| | ├──.gitignore 0.24kb
| | ├──.travis.yml 1.48kb
| | ├──combobox.py 0.94kb
| | ├──CONTRIBUTING.rst 0.08kb
| | ├──HISTORY.rst 1.37kb
| | ├──issue_template.md 0.14kb
| | ├──labelImg.py 59.51kb
| | ├──LICENSE 1.17kb
| | ├──Makefile 0.51kb
| | ├──MANIFEST.in 0.29kb
| | ├──README.rst 9.50kb
| | ├──resources.py 592.55kb
| | ├──resources.qrc 1.88kb
| | ├──setup.cfg 0.09kb
| | ├──setup.py 3.44kb
| | └──__init__.py
| ├──yolo-case
| | ├──.ipynb_checkpoints
| | ├──.specstory
| | ├──runs
| | ├──steel-data
| | ├──1-yolo-predict.ipynb 639.07kb
| | ├──2-yolo-train.ipynb 1.28M
| | ├──3-yolo-steel.ipynb 104.09kb
| | ├──4-yolo-steel-predict.ipynb 103.03kb
| | ├──coco-2.yaml 2.69kb
| | ├──coco.yaml 2.72kb
| | ├──convert_annotations.py 4.61kb
| | ├──submission.csv 33.79kb
| | ├──yolov12.yaml 1.92kb
| | └──yolov12n.pt 5.26M
| ├──1-Pytorch与视觉检测.pdf 8.29M
| └──笔记20251008.txt 3.96kb
├──25-项目实战：企业知识库
| ├──RAG-Challenge-2-main
| | ├──.ipynb_checkpoints
| | ├──.specstory
| | ├──data
| | ├──docs
| | ├──src
| | ├──.cursorindexingignore 0.11kb
| | ├──.gitignore 3.25kb
| | ├──1-情感分析-Qwen.py 0.75kb
| | ├──dashscope-embedding-1.py 0.69kb
| | ├──env 0.26kb
| | ├──LICENSE 1.04kb
| | ├──main.py 2.46kb
| | ├──README.md 3.50kb
| | ├──requirements.txt 0.49kb
| | ├──setup.py 0.10kb
| | └──运行情况.txt 26.01kb
| ├──RAG-cy
| | ├──.ipynb_checkpoints
| | ├──.specstory
| | ├──data
| | ├──docs
| | ├──src
| | ├──.cursorindexingignore 0.11kb
| | ├──.gitignore 3.25kb
| | ├──1-情感分析-Qwen.py 0.75kb
| | ├──dashscope-embedding-1.py 0.69kb
| | ├──env 0.26kb
| | ├──LICENSE 1.04kb
| | ├──main.py 2.46kb
| | ├──README.md 3.50kb
| | ├──requirements.txt 0.49kb
| | ├──setup.py 0.10kb
| | ├──UI界面参考.png 173.56kb
| | └──运行情况.txt 16.86kb
| ├──1-项目实战：企业知识库.pdf 2.82M
| └──笔记20251011.txt 13.75kb
├──26-项目实战：交互式BI报表
| ├──CASE-ChatBI助手
| | └──说明.txt 0.08kb
| ├──【完成参考】CASE-ChatBI助手
| | ├──.specstory
| | ├──image_show
| | ├──workspace
| | ├──.cursorindexingignore 0.11kb
| | ├──assistant_ticket_bot-3.py 8.59kb
| | ├──faq.txt 0.79kb
| | ├──requirements.txt 0.05kb
| | ├──stock_data.py 2.04kb
| | ├──stock_history_data.sql 1.02kb
| | ├──stock_history_data.xlsx 270.63kb
| | ├──stock_query_assistant-2.py 8.64kb
| | ├──stock_query_assistant-3.py 12.77kb
| | ├──stock_query_assistant-4.py 17.87kb
| | ├──stock_query_assistant-5.py 19.56kb
| | └──stock_query_assistant.py 7.77kb
| ├──1-项目实战：交互式BI报表.pdf 7.05M
| └──笔记20251015.txt 5.84kb
├──27-项目实战：AI运营助手
| ├──BreadBasket
| | ├──apriori_breadbasket.py 2.10kb
| | └──BreadBasket_DMS.csv 671.85kb
| ├──CASE-百万客群经营
| | ├──create_sql.sql 3.41kb
| | ├──customer_base.csv 1.61M
| | ├──customer_behavior_assets.csv 24.59M
| | └──项目说明.txt 0.69kb
| ├──【完成参考】CASE-百万客群经营
| | ├──image_show
| | ├──static
| | ├──templates
| | ├──workspace
| | ├──1-情感分析-Qwen.py 0.77kb
| | ├──apriori_product_combination.py 1.67kb
| | ├──arima_asset_trend.py 3.22kb
| | ├──aum_forecast.png 82.12kb
| | ├──aum_history.png 77.75kb
| | ├──bank_customer_assistant.py 12.26kb
| | ├──clustering_customer_segmentation.py 2.58kb
| | ├──coefficient_bar.png 42.94kb
| | ├──customer_base.csv 1.85M
| | ├──customer_behavior_assets.csv 29.14M
| | ├──customer_clusters.png 96.71kb
| | ├──customer_cluster_result.csv 74.67kb
| | ├──dashboard_app.py 5.00kb
| | ├──decision_tree_high_value.py 2.90kb
| | ├──frequent_product_itemsets.csv 0.80kb
| | ├──lgbm_feature_importance.png 31.87kb
| | ├──lgbm_high_value_model.txt 122.61kb
| | ├──LightGBM-SHAP解释.md 2.40kb
| | ├──lightgbm_high_value.py 3.22kb
| | ├──lightgbm_high_value_predict.py 1.51kb
| | ├──LightGBM解释.md 1.96kb
| | ├──logistic_regression_high_value.py 3.75kb
| | ├──product_association_rules.csv 5.40kb
| | ├──read_data.py 0.60kb
| | ├──shap_force_plot.png 65.83kb
| | ├──shap_lightgbm_high_value.py 3.30kb
| | ├──shap_summary_plot.png 68.87kb
| | ├──simulated_customers.xlsx 8.31kb
| | ├──simulated_customers_explain.py 2.16kb
| | ├──simulated_customers_with_explain.xlsx 9.34kb
| | ├──simulate_customers_and_predict.py 2.55kb
| | ├──tree_depth4.png 203.32kb
| | ├──决策树解释.md 1.82kb
| | ├──客户话术.xlsx 5.60kb
| | ├──客户话术生成.py 0.86kb
| | ├──客户数据库建表.sql 2.88kb
| | ├──课题说明.md 2.29kb
| | ├──逻辑回归解释.md 2.42kb
| | ├──数据表字段含义.md 3.96kb
| | └──智能助手问题集.md 3.20kb
| ├──笔记20251018.txt 12.15kb
| ├──挖掘数据中的关联关系.pdf 1.30M
| └──项目实战：AI运营助手.pdf 9.28M
├──28-项目实战：AI搜索类应用
| ├──CASE-AI搜索问答
| | ├──docs
| | ├──__pycache__
| | ├──ai_bot-1.py 6.66kb
| | ├──block_api_demo1.py 0.42kb
| | ├──logo.png 4.23kb
| | └──知乎直答.png 398.64kb
| ├──CASE-Qwen-Agent最佳实践
| | ├──.specstory
| | ├──workspace
| | ├──.cursorindexingignore 0.11kb
| | ├──1-long_dialogue.py 1.04kb
| | ├──2-parallel_doc_qa.py 1.26kb
| | ├──3-gpt_mentions.py 1.47kb
| | └──4-multi_agent_router_cn.py 3.01kb
| ├──【完成参考】CASE-AI搜索问答
| | ├──docs
| | ├──qwen_agent
| | ├──static
| | ├──__pycache__
| | ├──.cursorindexingignore 0.11kb
| | ├──ai_bot-1.py 6.66kb
| | ├──ai_bot-2.py 6.85kb
| | ├──ai_bot-3.py 2.69kb
| | ├──ai_bot-4.py 3.33kb
| | ├──ai_bot-5.py 8.75kb
| | ├──ai_bot-6.py 7.56kb
| | ├──ai_bot-7.py 7.33kb
| | ├──ai_bot-8.py 7.82kb
| | ├──ai_bot-9.py 8.24kb
| | ├──block_api_demo1.py 0.42kb
| | ├──es_retrieval_tool.py 8.44kb
| | ├──index_and_search_docs-embedding.py 6.72kb
| | ├──index_and_search_docs.py 4.79kb
| | ├──qwen-agent-multi-files-gui.py 6.66kb
| | ├──qwen-agent-multi-files.py 3.84kb
| | ├──qwen3-embedding.py 0.66kb
| | ├──simple_es_test.py 3.97kb
| | ├──stock_query_assistant-3.py 14.84kb
| | ├──test_es_retrieval.py 3.18kb
| | ├──test_es_single_file.py 8.72kb
| | └──知乎直答.png 398.64kb
| └──1-项目实战：AI搜索类应用.pdf 7.91M
├──3-Cursor编程-从入门到精通
| ├──CASE-bed_usage
| | └──hospital_bed_usage_data.xlsx 3.07M
| ├──CASE-dashboard_epidemic
| | └──香港各区疫情数据_20250322.xlsx 220.66kb
| ├──CASE-Excel_merge
| | ├──员工基本信息表.xlsx 9.48kb
| | └──员工绩效表.xlsx 6.69kb
| ├──【完成参考】bed_usage
| | ├──.qodo
| | ├──charts
| | ├──data_cache
| | ├──templates
| | ├──.gitignore 0.01kb
| | ├──app.py 20.70kb
| | ├──hospital_bed_usage_data.xlsx 3.07M
| | ├──precompute_data.py 8.07kb
| | ├──README.md 1.45kb
| | ├──requirements.txt 0.06kb
| | └──view_excel_data.py 7.18kb
| ├──【完成参考】dashboard_epidemic
| | ├──static
| | ├──templates
| | ├──.gitignore 0.01kb
| | ├──app.py 7.53kb
| | ├──README.md 1.70kb
| | ├──read_excel.py 7.98kb
| | ├──requirements.txt 0.06kb
| | ├──各地区确诊病例对比图.png 264.18kb
| | ├──活跃病例数据统计图.png 202.23kb
| | ├──每日确诊数据统计图.png 349.87kb
| | ├──香港各区疫情数据_20250322.xlsx 183.64kb
| | ├──疫情数据统计图 – 副本.png 179.12kb
| | └──疫情数据统计图.png 179.12kb
| ├──【完成参考】Excel_merge
| | ├──.qodo
| | ├──.gitignore 0.01kb
| | ├──test1.py 1.25kb
| | ├──员工基本信息表.xlsx 9.48kb
| | ├──员工绩效表.xlsx 6.69kb
| | └──员工信息与绩效合并表.xlsx 6.26kb
| ├──1-Cursor编程.pdf 3.91M
| ├──2-Trae与CodeBuddy.pdf 1.63M
| ├──3-Claude 4.pdf 307.66kb
| ├──【补充】CASE-病床使用情况.pdf 1.83M
| ├──【课前准备】AI编程工具安装.pdf 136.31kb
| └──笔记20250727.txt 6.86kb
├──4-Embeddings和向量数据库
| ├──Case-ChatPDF-Faiss
| | ├──.ipynb_checkpoints
| | ├──.qodo
| | ├──chatpdf-faiss.ipynb 18.05kb
| | ├──chatpdf-faiss.py 3.90kb
| | └──浦发上海浦东发展银行西安分行个金客户经理考核办法.pdf 323.28kb
| ├──CASE-向量数据库
| | ├──1-embedding计算.py 0.57kb
| | └──2-embedding-faiss-元数据.py 4.98kb
| ├──hotel_recommendation
| | ├──hotel_rec.ipynb 142.59kb
| | ├──hotel_rec.py 5.55kb
| | ├──requirements.txt 0.08kb
| | └──Seattle_Hotels.csv 155.59kb
| ├──word2vec
| | ├──.ipynb_checkpoints
| | ├──journey_to_the_west
| | ├──models
| | ├──three_kingdoms
| | ├──utils
| | ├──requirements.txt 0.08kb
| | ├──word_seg.py 1.11kb
| | └──word_similarity.py 1.14kb
| ├──1-Embedding与向量数据库.pdf 1.60M
| └──笔记20250730.txt 1.42kb
├──5-RAG技术与应用
| ├──CASE-ChatPDF-Faiss
| | ├──.ipynb_checkpoints
| | ├──faiss-1
| | ├──vector_db
| | ├──chatpdf-faiss.ipynb 22.07kb
| | ├──chatpdf-faiss.py 7.43kb
| | └──浦发上海浦东发展银行西安分行个金客户经理考核办法.pdf 323.28kb
| ├──CASE-embedding使用
| | ├──bge-m3使用.ipynb 15.85kb
| | ├──bge-m3使用.py 1.16kb
| | ├──gte-qwen2-使用1.ipynb 12.10kb
| | ├──gte-qwen2-使用1.py 1.45kb
| | ├──gte-qwen2-使用2.ipynb 3.92kb
| | └──gte-qwen2-使用2.py 4.66kb
| ├──CASE-迪士尼RAG助手
| | ├──disney_knowledge_base
| | ├──迪士尼RAG知识库
| | ├──1-disney_bot.ipynb 26.97kb
| | ├──1-disney_bot.py 13.53kb
| | ├──1-固定长度切片.ipynb 6.19kb
| | ├──1-固定长度切片.py 3.07kb
| | ├──2-万圣节.jpeg 73.42kb
| | ├──2-语义切片.ipynb 6.07kb
| | ├──2-语义切片.py 3.16kb
| | ├──3-LLM语义切片.ipynb 6.21kb
| | ├──3-LLM语义切片.py 4.78kb
| | ├──4-层次切片.ipynb 10.51kb
| | ├──4-层次切片.py 5.74kb
| | ├──5-滑动窗口切片.ipynb 6.11kb
| | ├──5-滑动窗口切片.py 2.66kb
| | ├──6-Qwen-VL图像理解.ipynb 2.80kb
| | ├──6-Qwen-VL图像理解.py 0.62kb
| | └──tesseract-ocr-w64-setup-5.5.0.20241111.exe 20.39M
| ├──1-RAG技术与应用.pdf 2.43M
| └──笔记20250802.txt 7.67kb
├──6-RAG高级技术与最佳实践
| ├──Case-ChatPDF-Faiss
| | ├──.ipynb_checkpoints
| | ├──faiss-1
| | ├──vector_db
| | ├──.gitignore 0.01kb
| | ├──chatpdf-faiss-MultiQueryRetriever.ipynb 18.30kb
| | ├──chatpdf-faiss-MultiQueryRetriever.py 9.49kb
| | ├──chatpdf-faiss.ipynb 32.38kb
| | ├──chatpdf-faiss.py 8.05kb
| | ├──MultiQueryRetriever使用.ipynb 6.70kb
| | ├──MultiQueryRetriever使用.py 1.31kb
| | ├──requirements.txt 0.09kb
| | └──浦发上海浦东发展银行西安分行个金客户经理考核办法.pdf 323.28kb
| ├──CASE-知识库处理
| | ├──1-知识库问题生成与检索优化-BM25.py 21.18kb
| | ├──2-对话知识沉淀.py 12.72kb
| | ├──3-知识库健康度检查.py 15.73kb
| | └──4-知识库版本管理与性能比较.py 20.71kb
| ├──CASEA-Query改写
| | ├──1-Query改写.py 10.52kb
| | └──2-Query联网搜索改写.py 9.18kb
| ├──graphrag-main
| | ├──cases
| | └──requirements.txt 0.41kb
| ├──rerank
| | ├──beg-reranker.ipynb 8.72kb
| | ├──beg-reranker.py 1.21kb
| | ├──gte-qwen2-使用1.ipynb 12.10kb
| | ├──gte-qwen2-使用1.py 1.45kb
| | └──requirements.txt 0.05kb
| ├──1-RAG高级技术与实践.pdf 4.12M
| └──笔记20250806.txt 6.29kb
├──7-Text2SQL：自助式数据报表开发
| ├──CASE-SQL Copilot
| | ├──.ipynb_checkpoints
| | ├──insurance
| | ├──codegeex-1.ipynb 8.44kb
| | └──qwen-coder1.ipynb 6.06kb
| ├──Case-SQL-LangChain
| | ├──.ipynb_checkpoints
| | ├──requirements.txt 0.08kb
| | ├──sql_agent_deepseek.ipynb 24.74kb
| | ├──sql_agent_deepseek.py 1.63kb
| | ├──sql_life_insurance.ipynb 23.21kb
| | └──sql_life_insurance.py 1.48kb
| ├──CASE-SQL-vanna
| | ├──.ipynb_checkpoints
| | ├──6964cc59-7b4f-4f30-ab63-34301bf46276
| | ├──6e991d67-8a72-474d-b791-efc3f1d64649
| | ├──e5f6b279-ba5a-4c79-8c60-e4946424ecd0
| | ├──1-情感分析-Qwen.py 0.82kb
| | ├──chroma.sqlite3 496.00kb
| | ├──requirements.txt 0.06kb
| | ├──vanna-mysql.ipynb 33.17kb
| | └──vanna-mysql.py 3.13kb
| ├──SQL数据表源文件
| | ├──agentinfo.sql 235.42kb
| | ├──beneficiaryinfo.sql 140.62kb
| | ├──claiminfo.sql 271.36kb
| | ├──crs_orders.sql 4.98kb
| | ├──customerinfo.sql 266.22kb
| | ├──employeeinfo.sql 303.85kb
| | ├──heros.sql 14.66kb
| | ├──policyinfo.sql 242.63kb
| | └──productinfo.sql 201.10kb
| ├──1-Text2SQL：自助式数据报表开发.pdf 3.08M
| ├──2-vanna使用.pdf 479.21kb
| └──笔记20250809.txt 8.43kb
├──8-LangChain：多任务应用开发
| ├──CASE-LangChain使用
| | ├──.ipynb_checkpoints
| | ├──1-LLMChain.ipynb 3.44kb
| | ├──1-LLMChain.py 0.80kb
| | ├──2-LLMChain.ipynb 7.24kb
| | ├──2-LLMChain.py 1.73kb
| | ├──3-LLMChain.ipynb 9.06kb
| | ├──3-LLMChain.py 1.87kb
| | ├──4-ConversationChain.ipynb 4.35kb
| | ├──4-ConversationChain.py 0.83kb
| | └──5-product_llm.py 8.53kb
| ├──CASE-搭建故障诊断Agent
| | ├──2-network_diagnosis_agent.md 2.80kb
| | ├──2-network_diagnosis_agent.py 10.75kb
| | └──network_diagnosis_agent_logic.md 5.46kb
| ├──CASE-工具链组合
| | ├──1-simple_toolchain.py 9.25kb
| | ├──2-simple_toolchain.py 7.96kb
| | └──3-lcel-demo.py 1.22kb
| ├──1-LangChain：多任务应用开发.pdf 3.04M
| └──笔记20250813.txt 7.92kb
├──9-Function Calling与协作
| ├──CASE-Function Calling
| | ├──assistant_weather_bot-1.py 6.38kb
| | ├──qwen3-function使用-2.py 5.60kb
| | ├──qwen3-function使用.py 2.86kb
| | └──requirements.txt 0.11kb
| ├──CASE-ticket-agent
| | ├──workspace
| | ├──assistant_revenue_bot.py 22.15kb
| | ├──assistant_ticket_bot-1.py 6.74kb
| | ├──assistant_ticket_bot-2.py 8.95kb
| | ├──assistant_ticket_bot-3.py 9.80kb
| | └──requirements.txt 0.15kb
| ├──Function Calling与协作.pdf 2.08M
| └──笔记20250816.txt 8.39kb
└──开营直播
| ├──0720学习路径与规划.pdf 2.47M
| └──笔记20250720.txt 0.22kb