AI大模型15期大课 百度网盘打包下载

  大模型15期/

├──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

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