zh大模型14期【vip】
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├──0-AI大模型第14期正课【视频课文件夹】
| ├──11、Agent智能体系统的设计与应用.mp4361.94M
| ├──12、MCP应用与实战.mp4337.00M
| ├──13、视觉大模型与视觉智能体.mp4387.74M
| ├──14、Fine-tuning技术与大模型优化.mp4422.64M
| ├──15、Coze工作原理与应用实例.mp4355.48M
| ├──16、Coze插件开发实战.mp4400.16M
| ├──17、Dify本地化部署和应用.mp4347.05M
| ├──18、分析式AI基础.mp4413.35M
| ├──20、机器学习神器.mp4353.04M
| ├──21、时间序列模型.mp4358.62M
| ├──22、时间序列AI大赛.mp4384.27M
| ├──23、项目实战：交互式BI报表.mp4444.49M
| ├──24、项目实战：企业知识库.mp4428.06M
| ├──25、项目实战：AI运营助手.mp4455.50M
| ├──26、项目实战：AI搜索类应用.mp4545.67M
| ├──5、Embeddings和向量数据库.mp4322.15M
| ├──6、RAG（Retrieval Augmented Generation）技术与应用.mp4371.50M
| ├──7、RAG高级技术与最佳实践.mp4407.65M
| ├──8、Text2SQL：自助式数据报表开发.mp4398.10M
| ├──9、LangChain：多任务应用开发.mp4400.06M
| ├──0、开班典礼.mp4318.15M
| ├──10、Function Calling与跨模型协作.mp4377.94M
| ├──19、不同领域的AI算法.mp4354.20M
| ├──1、AI大模型基本原理与deepseek使用.mp4400.13M
| ├──2、Prompt工程：设计与优化.mp4345.95M
| ├──3、Cursor编程-从入门到精通.mp4344.70M
| └──4、Cursor 可视化大屏搭建.mp4294.73M
├──1-AI大模型原理与API使用
| ├──CASE-保险反欺诈
| | ├──.ipynb_checkpoints
| | ├──test.csv78.23kb
| | └──train.csv183.49kb
| ├──3-表格提取-Qwen.ipynb5.06kb
| ├──4-运维事件处置-Qwen.ipynb6.14kb
| ├──5-情感分析-Deepseek-阿里代理.ipynb1.70kb
| ├──6-deepseek-r1-7b使用.ipynb6.62kb
| ├──6-deepseek-r1-7b使用.py0.97kb
| ├──README.md2.11kb
| ├──1-AI大模型原理与DeepSeek使用.pdf3.01M
| ├──1-情感分析-Qwen.ipynb1.71kb
| ├──2-API使用.pdf1.59M
| ├──2-天气Function-Qwen.ipynb6.84kb
| └──笔记-20250331.txt2.66kb
├──10-Function Callling与协作
| ├──CASE-Function Calling
| | ├──qwen3-function使用-2.py5.60kb
| | ├──qwen3-function使用.py2.86kb
| | └──requirements.txt0.04kb
| ├──CASE-ticket-agent
| | ├──assistant_revenue_bot.py22.15kb
| | ├──assistant_ticket_bot-1.py6.74kb
| | ├──assistant_ticket_bot-2.py8.95kb
| | ├──assistant_ticket_bot-3.py9.80kb
| | └──requirements.txt0.13kb
| └──Function Calling与协作.pdf1.74M
├──10-Function Callling与协作(1)
| ├──CASE-Function Calling
| | ├──assistant_weather_bot-1.py6.38kb
| | ├──qwen3-function使用-2.py5.60kb
| | ├──qwen3-function使用.py2.86kb
| | └──requirements.txt0.04kb
| ├──CASE-ticket-agent
| | ├──assistant_revenue_bot.py22.15kb
| | ├──assistant_ticket_bot-1.py6.74kb
| | ├──assistant_ticket_bot-2.py8.95kb
| | ├──assistant_ticket_bot-3.py9.80kb
| | └──requirements.txt0.13kb
| ├──Function Calling与协作.pdf2.08M
| └──笔记20250506.txt8.79kb
├──11-MCP与A2A应用
| ├──CASE-A2A使用
| | ├──BasketBallAgent.py2.01kb
| | ├──requirements.txt0.07kb
| | └──WeatherAgent.py1.79kb
| ├──CASE-MCP Demo-1
| | ├──.cursorindexingignore0.11kb
| | ├──.gitignore0.01kb
| | ├──assistant_mcp_amap_bot.py6.30kb
| | ├──assistant_mcp_txt_bot.py6.21kb
| | ├──requirements.txt0.05kb
| | ├──txt_counter.py2.02kb
| | └──旅行规划.md4.60kb
| ├──CASE-MCP Demo-2
| | ├──assistant_bot.py6.21kb
| | └──requirements.txt0.04kb
| ├──1-MCP与A2A的应用.pdf5.69M
| └──笔记20250508.txt3.82kb
├──12-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.py13.80kb
| | └──fund_qa_qwen_agent.py7.17kb
| ├──CASE-投顾AI助手（混合式）
| | ├──hybrid_wealth_advisor_langgraph.py22.90kb
| | ├──hybrid_wealth_advisor_qwen_agent.py16.79kb
| | └──requirements.txt0.16kb
| ├──CASE-智能投研助手（深思熟虑）
| | ├──deliberative_research_agent_comparison.md5.38kb
| | ├──deliberative_research_agent_documentation.md8.82kb
| | ├──deliberative_research_langgraph.py18.42kb
| | ├──deliberative_research_qwen_agent-2.py19.50kb
| | └──requirements.txt0.13kb
| ├──1-Agent智能体系统的设计与应用.pdf2.79M
| └──笔记20250513.txt8.11kb
├──13-视觉大模型与多模态理解
| ├──CASE-MinerU使用
| | ├──1-MinerU.ipynb3.06kb
| | ├──download_models_hf.py2.40kb
| | ├──Qwen3-tech_report.pdf6.09M
| | └──三国演义.pdf3.75M
| ├──CASE-VLM在车险中的应用
| | ├──.ipynb_checkpoints
| | ├──4-Dangerous-driving-behavior-detection.jpg43.33kb
| | ├──5-Dangerous-driving-behavior-detection.jpg29.72kb
| | ├──6-Dangerous-driving-behavior-detection-1.jpg19.83kb
| | ├──6-Dangerous-driving-behavior-detection-2.jpg20.10kb
| | ├──6-Dangerous-driving-behavior-detection-3.jpg19.42kb
| | ├──6-Dangerous-driving-behavior-detection-4.jpg21.20kb
| | ├──6-Dangerous-driving-behavior-detection-5.jpg23.60kb
| | ├──prompt_template_cn.xlsx9.87kb
| | ├──prompt_template_cn_result-20250430.xlsx17.67kb
| | ├──prompt_template_cn_result.xlsx13.54kb
| | ├──prompt_template_en.xlsx9.73kb
| | ├──prompt_template_en_result.xlsx9.79kb
| | ├──1-Qwen-VL-保险识别-cn.ipynb23.78kb
| | ├──1-vehicle-odometer-reading.jpg22.40kb
| | ├──10-extraction-of-auto-accident-elements.jpg120.51kb
| | ├──11-vehicle-identity-verification-1.jpg47.79kb
| | ├──11-vehicle-identity-verification-2.jpg51.02kb
| | ├──12-vehicle-identity-verification-1.jpg60.98kb
| | ├──12-vehicle-identity-verification-2.jpg81.03kb
| | ├──2-Qwen-VL-chat1.ipynb893.20kb
| | ├──2-vehicle-odometer-reading.jpg86.14kb
| | ├──3-vehicle-underwriting-1.jpg38.94kb
| | ├──3-vehicle-underwriting-2.jpg44.99kb
| | ├──3-vehicle-underwriting-3.jpg46.13kb
| | ├──3-vehicle-underwriting-4.jpg41.67kb
| | ├──3-vehicle-underwriting-5.jpg32.84kb
| | ├──7-vehicle-damage-evaluation.jpg68.60kb
| | ├──8-vehicle-damage-evaluation.jpg42.22kb
| | └──9-extraction-of-auto-accident-elements.jpg74.18kb
| ├──CASE-VLM在寿险中的应用
| | ├──.ipynb_checkpoints
| | ├──1-Chinese-document-extraction.jpg80.99kb
| | ├──1-Qwen-VL-保险识别-cn.ipynb11.01kb
| | ├──2-Japanese-document-extraction.jpg173.05kb
| | ├──3-French-document-extraction.jpg202.74kb
| | ├──4-German-document-extraction.jpg142.75kb
| | ├──5-Korean-document-extraction.jpg117.13kb
| | ├──prompt_template_cn.xlsx9.10kb
| | ├──prompt_template_cn_result.xlsx7.88kb
| | └──2-Qwen-VL-本地图片.ipynb4.08kb
| ├──CASE-汽车剐蹭视频理解
| | ├──car.mp45.77M
| | ├──requirements.txt0.10kb
| | ├──video-understand.ipynb18.61kb
| | └──video-understand.py9.71kb
| ├──yolo-cases.zip80.75M
| ├──笔记20250515.txt2.80kb
| └──视觉大模型与多模态理解.pdf6.66M
├──14-Fine-tuning技术与大模型优化
| ├──【数据集】AdvertiseGen
| | ├──dev.json486.71kb
| | ├──dev2.json4.15kb
| | ├──train.json51.27M
| | └──train2.json92.67kb
| ├──【数据集】alpaca-cleaned
| | ├──alpaca_data_cleaned.json42.25M
| | ├──gitattributes2.27kb
| | └──README.md11.34kb
| ├──【数据集】gsm8k
| | ├──main
| | ├──socratic
| | ├──gitattributes1.57kb
| | ├──gsm8k.zip4.89M
| | └──README.md7.75kb
| ├──【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技术与大模型优化.pdf2.63M
| ├──2-金融垂类大模型（智能客服）.pdf455.23kb
| ├──Qwen2_5_(7B)_Alpaca-2.ipynb169.72kb
| ├──Qwen2_5_(7B)_R1.ipynb528.96kb
| ├──Qwen2_5_(7B)_模型调用.ipynb53.01kb
| ├──Qwen2_5_(7B)_医疗微调.ipynb685.16kb
| ├──requirements.txt0.23kb
| └──笔记20250520.txt7.86kb
├──15-Coze工作原理与应用实例
| ├──CASE：创建产品知识库
| | ├──大模型定价.xlsx8.75kb
| | ├──空调定价.xlsx8.64kb
| | ├──浦发上海浦东发展银行西安分行个金客户经理考核办法.pdf368.62kb
| | └──远程办公场景最佳实践.docx469.57kb
| ├──1-Coze工作原理与应用实例.pdf5.83M
| └──笔记20250522.txt5.93kb
├──16-Coze进阶实战与插件开发
| ├──CASE-客户分层营销助手
| | ├──user_behavior_event.xlsx9.96kb
| | ├──user_tag.xlsx9.19kb
| | └──营销策略.xlsx12.51kb
| ├──CASE-市场舆情监测Agent
| | ├──AppStorePast-代码1.py0.48kb
| | ├──AppStorePast.py1.05kb
| | ├──securities_past.py2.58kb
| | ├──代码.js1.22kb
| | └──代码1.py0.34kb
| ├──CASE-智能客服Agent
| | ├──user_complain.xlsx8.89kb
| | ├──港股交易规则介绍.pdf954.16kb
| | ├──平安财富日添利理财产品.doc30.00kb
| | ├──上海证券交易所交易规则.pdf378.09kb
| | └──中国平安金裕人生理财产品.doc61.00kb
| ├──ABC公司证券产品介绍.txt6.66kb
| ├──Coze进阶实战与插件开发.pdf6.40M
| ├──笔记20250527.txt4.40kb
| └──证券舆情Agent.mp44.44M
├──17-Dify本地化部署和应用
| ├──CASE-Coze API使用
| | ├──__pycache__
| | ├──config.py0.40kb
| | ├──coze_client.py9.10kb
| | └──requirements.txt0.04kb
| ├──CASE-Dify API使用
| | ├──__pycache__
| | ├──dify_agent_client.py19.92kb
| | ├──dify_workflow_example.py0.93kb
| | └──requirements.txt0.04kb
| ├──CASE-智能文档分析助手
| | └──INTERNVIDEO2.5.pdf1.84M
| └──1-Dify部署与应用.pdf4.18M
├──17-Dify本地化部署和应用(1)
| ├──CASE-Coze API使用
| | ├──__pycache__
| | ├──config.py0.40kb
| | ├──coze_client.py9.10kb
| | └──requirements.txt0.04kb
| ├──CASE-Dify API使用
| | ├──__pycache__
| | ├──chatpdf-faiss.py7.95kb
| | ├──dify_agent_client.py19.92kb
| | ├──dify_workflow_example.py0.93kb
| | └──requirements.txt0.04kb
| ├──CASE-智能客服ChatFlow
| | ├──user_behavior_event.xlsx9.96kb
| | ├──user_tag.xlsx9.19kb
| | ├──港股交易规则介绍.pdf954.16kb
| | ├──平安财富日添利理财产品.doc30.00kb
| | ├──上海证券交易所交易规则.pdf378.09kb
| | └──中国平安金裕人生理财产品.doc61.00kb
| ├──CASE-智能文档分析助手
| | └──INTERNVIDEO2.5.pdf1.84M
| ├──1-Dify部署与应用.pdf4.18M
| ├──DeepSeek-R1-0528.pdf534.43kb
| ├──LLM联网搜索0529.yml19.73kb
| ├──笔记20250529.txt1.80kb
| ├──古诗词绘画助手.yml14.55kb
| ├──智能客服ChatFlow.yml12.59kb
| └──智能文档助手0529.yml17.52kb
├──18-分析式AI基础
| ├──Case-二手车价格预测
| | ├──used_car_sample_submit.csv439.47kb
| | ├──used_car_testB_20200421.csv17.06M
| | └──used_car_train_20200313.csv51.77M
| ├──【完成参考】Case-二手车价格预测
| | ├──catboost_info
| | ├──processed_data
| | ├──.gitignore0.01kb
| | ├──brand_distribution.png19.15kb
| | ├──catboost_feature_importance.csv0.98kb
| | ├──catboost_feature_importance.png28.69kb
| | ├──catboost_prediction_vs_actual.png79.54kb
| | ├──catboost_submit_result.csv1.26M
| | ├──correlation_heatmap.png454.95kb
| | ├──data_preprocessing.py8.03kb
| | ├──ensemble_analysis.png74.16kb
| | ├──feature_engineering_and_catboost.py14.02kb
| | ├──feature_importance.csv0.85kb
| | ├──feature_importance.png28.14kb
| | ├──fe_catboost_feature_importance.csv2.25kb
| | ├──fe_catboost_feature_importance.png36.91kb
| | ├──fe_catboost_prediction_vs_actual.png80.19kb
| | ├──fe_catboost_submit_result.csv1.26M
| | ├──lightgbm_feature_importance.png29.07kb
| | ├──lightgbm_prediction_vs_actual.png80.01kb
| | ├──lightgbm_submit_result.csv1.26M
| | ├──model_ensemble.py3.74kb
| | ├──prediction_vs_actual.png78.76kb
| | ├──predict_catboost.py6.14kb
| | ├──price_distribution.png17.99kb
| | ├──price_vs_kilometer.png72.02kb
| | ├──price_vs_power.png47.34kb
| | ├──price_vs_v_0.png112.22kb
| | ├──price_vs_v_1.png140.78kb
| | ├──price_vs_v_2.png83.39kb
| | ├──submit_result-xgboost.csv861.07kb
| | ├──submit_result.csv1.26M
| | ├──train_catboost.py4.99kb
| | ├──train_lightgbm.py5.31kb
| | ├──train_xgboost.py4.65kb
| | ├──used_car_sample_submit.csv439.47kb
| | ├──used_car_testB_20200421.csv17.06M
| | ├──used_car_train_20200313.csv51.77M
| | ├──view_data.py4.29kb
| | └──特征工程.md3.51kb
| ├──1-分析式AI基础.pdf2.43M
| └──笔记20250603.txt4.02kb
├──19-不同领域的AI算法
| ├──【完成参考】Case-二手车价格预测
| | ├──.ipynb_checkpoints
| | ├──catboost_info
| | ├──processed_data
| | ├──eda_used_car.ipynb13.39kb
| | ├──eda_used_car.py2.56kb
| | ├──feature_engineering_and_catboost.ipynb106.57kb
| | ├──feature_engineering_and_catboost.py13.44kb
| | ├──fe_catboost_feature_importance.csv1.87kb
| | ├──fe_catboost_feature_importance.png34.75kb
| | ├──fe_catboost_prediction_vs_actual.png70.12kb
| | ├──used_car_sample_submit.csv439.47kb
| | ├──used_car_testB_20200421.csv17.06M
| | └──used_car_train_20200313.csv51.77M
| ├──1-不同领域的AI算法.pdf3.09M
| └──笔记20250605.txt10.13kb
├──2-Prompt工程：设计与优化
| ├──1-DeepSeek使用.pdf3.45M
| ├──1-情感分析-Deepseek-阿里代理.ipynb1.70kb
| ├──1-情感分析-Deepseek-阿里代理.py1.03kb
| ├──2-提示词工程.pdf1.17M
| ├──2-提示词工程使用.ipynb9.66kb
| ├──2-提示词工程使用.py3.70kb
| ├──3-deepseek-r1-7b使用.ipynb6.62kb
| ├──3-deepseek-r1-7b使用.py0.97kb
| ├──README.md1.77kb
| └──笔记20250403.txt4.41kb
├──20-机器学习神器
| ├──Attrition
| | ├──catboost_info
| | ├──attrition.csv183.15kb
| | ├──attrition_catboost.py2.25kb
| | ├──attrition_gbdt.py1.57kb
| | ├──attrition_lgb.py2.76kb
| | ├──attrition_lgb_onehot.py2.23kb
| | ├──attrition_lr.py3.10kb
| | ├──attrition_lr_threshold.py2.32kb
| | ├──attrition_ngboost.py1.64kb
| | ├──attrition_svc.py2.74kb
| | ├──attrition_xgboost.py2.12kb
| | ├──submit_cb.csv2.10kb
| | ├──submit_gbdt.csv7.29kb
| | ├──submit_lgb.csv2.10kb
| | ├──submit_lr.csv7.18kb
| | ├──submit_lr_threshold.csv2.10kb
| | ├──submit_ngb.csv2.10kb
| | ├──submit_svc.csv2.10kb
| | ├──submit_xgb.csv4.62kb
| | ├──test.csv45.18kb
| | ├──train.csv183.15kb
| | └──train_label_encoder.csv97.84kb
| ├──voice
| | ├──voice.csv1.02M
| | ├──voice_predict.ipynb107.84kb
| | └──voice_predict.py2.90kb
| ├──1-机器学习神器.pdf1.68M
| └──笔记20250610.txt5.92kb
├──21-时间序列模型
| ├──CASE-资金流入流出预测
| | ├──comp_predict_table.csv0.08kb
| | ├──mfd_bank_shibor.csv19.06kb
| | ├──mfd_day_share_interest.csv9.53kb
| | ├──user_balance_table.csv150.45M
| | └──user_profile_table.csv728.55kb
| ├──sales_prediction
| | ├──.ipynb_checkpoints
| | ├──predict1.ipynb37.35kb
| | ├──sales.csv0.64kb
| | └──sales_prediction.py2.99kb
| ├──stock
| | ├──.ipynb_checkpoints
| | ├──.qodo
| | ├──.gitignore0.01kb
| | ├──1-stock_tsa.ipynb87.40kb
| | ├──1-stock_tsa.py0.73kb
| | ├──2-arma-demo.ipynb179.94kb
| | ├──2-arma_demo.py1.36kb
| | ├──3-stock_arma.ipynb289.04kb
| | ├──4-stock_arima.ipynb164.45kb
| | ├──4-stock_arima.py2.99kb
| | ├──5-stock_prophet.ipynb160.24kb
| | ├──688692_SH_close_price.png58.81kb
| | ├──688692_SH_daily_data.csv16.93kb
| | ├──688692_SH_full_prediction.png69.79kb
| | ├──688692_SH_model_fit_seasonal.png100.82kb
| | ├──688692_SH_prediction_seasonal.png56.80kb
| | ├──688692_SH_prediction_seasonal_results.csv0.59kb
| | ├──download_688692SH.py2.44kb
| | ├──download_688692SH_alt.py3.70kb
| | ├──predict_688692SH.py5.90kb
| | ├──predict_688692SH_prophet.py6.22kb
| | ├──predict_688692SH_seasonal.py6.78kb
| | ├──README.md2.20kb
| | ├──run_all_predictions.py7.66kb
| | ├──shanghai_index_1990_12_19_to_2020_03_12.csv270.06kb
| | ├──stock_arima.py3.08kb
| | ├──stock_arma.py3.16kb
| | ├──stock_lstm.py4.25kb
| | ├──stock_prophet.py1.06kb
| | └──stock_tsa.py0.65kb
| ├──1-时间序列分析.pdf1.96M
| └──笔记20250612.txt6.81kb
├──22-时间序列AI大赛
| ├──CASE-资金流入流出预测
| | ├──boxplot_weekday.py1.59kb
| | ├──comp_predict_table.csv0.08kb
| | ├──cycle_factor_predict.py1.87kb
| | ├──mfd_bank_shibor.csv19.06kb
| | ├──mfd_day_share_interest.csv9.53kb
| | ├──predict.py3.59kb
| | ├──predict_prophet.py4.38kb
| | ├──user_balance_table.csv150.45M
| | └──user_profile_table.csv728.55kb
| ├──jetrail
| | ├──jetrail_prophet.py0.90kb
| | └──train.csv477.59kb
| ├──manning
| | ├──.ipynb_checkpoints
| | ├──manning.csv84.81kb
| | ├──manning_prophet.ipynb1.17M
| | ├──manning_prophet.py3.44kb
| | ├──突变点检测.ipynb165.16kb
| | └──突变点检测.py1.65kb
| ├──stock
| | ├──.ipynb_checkpoints
| | ├──arma_demo.py1.26kb
| | ├──shanghai_index_1990_12_19_to_2020_03_12.csv270.06kb
| | ├──stock_arima.py3.08kb
| | ├──stock_arma.py3.16kb
| | ├──stock_lstm.py4.25kb
| | ├──stock_prophet.ipynb243.75kb
| | ├──stock_prophet.py1.01kb
| | └──stock_tsa.py0.65kb
| ├──笔记20250617.txt7.38kb
| └──时间序列AI大赛.pdf1.61M
├──23-项目实战：企业知识库
| ├──RAG-Challenge-2-main
| | ├──.ipynb_checkpoints
| | ├──.specstory
| | ├──data
| | ├──docs
| | ├──src
| | ├──.cursorindexingignore0.11kb
| | ├──.gitignore3.25kb
| | ├──1-情感分析-Qwen.py0.75kb
| | ├──dashscope-embedding-1.py0.69kb
| | ├──env0.26kb
| | ├──LICENSE1.04kb
| | ├──main.py2.46kb
| | ├──README.md3.50kb
| | ├──requirements.txt0.49kb
| | ├──setup.py0.10kb
| | └──运行情况.txt26.01kb
| ├──RAG-cy
| | ├──.ipynb_checkpoints
| | ├──.specstory
| | ├──data
| | ├──docs
| | ├──src
| | ├──.cursorindexingignore0.11kb
| | ├──.gitignore3.25kb
| | ├──1-情感分析-Qwen.py0.75kb
| | ├──app_streamlit.py3.52kb
| | ├──dashscope-embedding-1.py0.69kb
| | ├──env0.26kb
| | ├──LICENSE1.04kb
| | ├──main.py2.46kb
| | ├──README.md3.50kb
| | ├──requirements.txt0.49kb
| | ├──setup.py0.10kb
| | ├──UI界面参考.png173.56kb
| | └──运行情况.txt16.86kb
| ├──1-项目实战：企业知识库.pdf2.82M
| └──笔记20250619.txt16.54kb
├──24-项目实战：交互式BI报表
| ├──CASE-ChatBI助手
| | └──说明.txt0.08kb
| ├──【完成参考】CASE-ChatBI助手
| | ├──.specstory
| | ├──image_show
| | ├──workspace
| | ├──.cursorindexingignore0.11kb
| | ├──assistant_ticket_bot-3.py8.59kb
| | ├──faq.txt0.79kb
| | ├──README_CN.md12.36kb
| | ├──requirements.txt0.05kb
| | ├──stock_data.py2.04kb
| | ├──stock_history_data.sql1.02kb
| | ├──stock_history_data.xlsx270.63kb
| | ├──stock_query_assistant-2.py8.64kb
| | ├──stock_query_assistant-3.py12.77kb
| | ├──stock_query_assistant-4.py17.87kb
| | ├──stock_query_assistant-5.py19.56kb
| | └──stock_query_assistant.py7.77kb
| ├──1-项目实战：交互式BI报表.pdf7.05M
| └──笔记20250624.txt5.90kb
├──25-项目实战：AI运营助手
| ├──BreadBasket
| | ├──apriori_breadbasket.py2.10kb
| | └──BreadBasket_DMS.csv671.85kb
| ├──CASE-百万客群经营
| | ├──create_sql.sql3.41kb
| | ├──customer_base.csv1.61M
| | ├──customer_behavior_assets.csv24.59M
| | └──项目说明.txt0.69kb
| ├──【完成参考】CASE-百万客群经营
| | ├──image_show
| | ├──static
| | ├──templates
| | ├──workspace
| | ├──1-情感分析-Qwen.py0.77kb
| | ├──apriori_product_combination.py1.67kb
| | ├──arima_asset_trend.py3.22kb
| | ├──aum_forecast.png82.12kb
| | ├──aum_history.png77.75kb
| | ├──bank_customer_assistant.py12.26kb
| | ├──clustering_customer_segmentation.py2.58kb
| | ├──customer_base.csv1.85M
| | ├──customer_behavior_assets.csv29.14M
| | ├──customer_clusters.png96.71kb
| | ├──customer_cluster_result.csv74.67kb
| | ├──dashboard_app.py5.00kb
| | ├──decision_tree_high_value.py2.90kb
| | ├──frequent_product_itemsets.csv0.80kb
| | ├──lgbm_feature_importance.png31.87kb
| | ├──lgbm_high_value_model.txt122.61kb
| | ├──LightGBM-SHAP解释.md2.40kb
| | ├──simulated_customers_explain.py2.16kb
| | ├──simulated_customers_with_explain.xlsx9.34kb
| | ├──simulate_customers_and_predict.py2.55kb
| | ├──tree_depth4.png203.32kb
| | ├──coefficient_bar.png42.94kb
| | ├──lightgbm_high_value.py3.22kb
| | ├──lightgbm_high_value_predict.py1.51kb
| | ├──LightGBM解释.md1.96kb
| | ├──logistic_regression_high_value.py3.75kb
| | ├──product_association_rules.csv5.40kb
| | ├──read_data.py0.60kb
| | ├──shap_force_plot.png65.83kb
| | ├──shap_lightgbm_high_value.py3.30kb
| | ├──shap_summary_plot.png68.87kb
| | ├──simulated_customers.xlsx8.31kb
| | ├──决策树解释.md1.82kb
| | ├──客户话术.xlsx5.60kb
| | ├──客户话术生成.py0.86kb
| | ├──客户数据库建表.sql2.88kb
| | ├──课题说明.md2.29kb
| | ├──逻辑回归解释.md2.42kb
| | ├──数据表字段含义.md3.96kb
| | └──智能助手问题集.md3.20kb
| ├──magicOrb.js13.55kb
| ├──笔记20250626.txt8.04kb
| └──项目实战：AI运营助手.pdf9.10M
├──26-项目实战：AI搜索类应用
| ├──CASE-AI搜索问答
| | ├──docs
| | ├──__pycache__
| | ├──ai_bot-1.py6.66kb
| | ├──block_api_demo1.py0.42kb
| | ├──logo.png4.23kb
| | └──知乎直答.png398.64kb
| ├──CASE-Qwen-Agent最佳实践
| | ├──1-long_dialogue.py1.04kb
| | ├──2-parallel_doc_qa.py1.26kb
| | ├──3-gpt_mentions.py1.47kb
| | └──4-multi_agent_router_cn.py3.01kb
| ├──【完成参考】CASE-AI搜索问答
| | ├──docs
| | ├──qwen_agent
| | ├──static
| | ├──__pycache__
| | ├──.cursorindexingignore0.11kb
| | ├──ai_bot-1.py6.66kb
| | ├──ai_bot-2.py6.85kb
| | ├──ai_bot-3.py2.69kb
| | ├──ai_bot-4.py3.33kb
| | ├──ai_bot-5.py8.75kb
| | ├──ai_bot-6.py7.56kb
| | ├──ai_bot-7.py7.33kb
| | ├──ai_bot-8.py7.82kb
| | ├──ai_bot-9.py8.24kb
| | ├──block_api_demo1.py0.42kb
| | ├──es_retrieval_tool.py8.44kb
| | ├──index_and_search_docs-embedding.py6.72kb
| | ├──index_and_search_docs.py4.79kb
| | ├──qwen-agent-multi-files-gui.py6.66kb
| | ├──qwen-agent-multi-files.py3.84kb
| | ├──qwen3-embedding.py0.66kb
| | ├──simple_es_test.py3.97kb
| | ├──stock_query_assistant-3.py14.84kb
| | ├──test_es_retrieval.py3.18kb
| | ├──test_es_single_file.py8.72kb
| | └──知乎直答.png398.64kb
| ├──1-项目实战：AI搜索类应用.pdf7.91M
| └──笔记20250701.txt11.91kb
├──3-Cursor编程：从入门到精通
| ├──CASE-bed_usage
| | ├──.qodo
| | └──hospital_bed_usage_data.xlsx3.07M
| ├──CASE-dashboard_epidemic
| | └──香港各区疫情数据_20250322.xlsx183.64kb
| ├──CASE-Excel_merge
| | ├──员工基本信息表.xlsx9.48kb
| | └──员工绩效表.xlsx6.69kb
| ├──【完成参考】bed_usage
| | ├──.qodo
| | ├──charts
| | ├──data_cache
| | ├──templates
| | ├──.gitignore0.01kb
| | ├──app.py20.70kb
| | ├──hospital_bed_usage_data.xlsx3.07M
| | ├──precompute_data.py8.07kb
| | ├──README.md1.45kb
| | └──view_excel_data.py7.18kb
| ├──【完成参考】dashboard_epidemic
| | ├──.git
| | ├──.qodo
| | ├──static
| | ├──templates
| | ├──.gitignore0.01kb
| | ├──app.py7.53kb
| | ├──README.md1.70kb
| | ├──read_excel.py7.98kb
| | ├──requirements.txt0.06kb
| | ├──各地区确诊病例对比图.png264.18kb
| | ├──活跃病例数据统计图.png202.23kb
| | ├──每日确诊数据统计图.png349.87kb
| | ├──香港各区疫情数据_20250322.xlsx183.64kb
| | ├──疫情数据统计图 - 副本.png179.12kb
| | └──疫情数据统计图.png179.12kb
| ├──【完成参考】Excel_merge
| | ├──.qodo
| | ├──.gitignore0.01kb
| | ├──Excel_merge.py1.25kb
| | ├──员工基本信息表.xlsx9.48kb
| | ├──员工绩效表.xlsx6.69kb
| | └──员工信息与绩效合并表.xlsx6.26kb
| ├──1-Cursor编程.pdf3.91M
| ├──【补充】CASE-病床使用情况.pdf1.83M
| ├──【课前准备】AI编程工具安装.pdf131.73kb
| └──笔记20250408.txt7.27kb
├──4-Cursor数据可视化与洞察
| ├──CASE-客户续保预测
| | ├──policy_data.xlsx93.93kb
| | └──policy_test.xlsx25.09kb
| ├──【完成参考】CASE-客户续保预测
| | ├──.qodo
| | ├──.gitignore0.01kb
| | ├──age_distribution.png16.25kb
| | ├──analyze_data.py3.13kb
| | ├──best_decision_tree_text.txt2.83kb
| | ├──best_decision_tree_viz.png657.00kb
| | ├──best_dt_roc_curve.png39.14kb
| | ├──best_lr_coefficients.png46.71kb
| | ├──best_lr_feature_importance.png32.37kb
| | ├──best_lr_roc_curve.png36.37kb
| | ├──best_roc_curve.png35.87kb
| | ├──bnb_confusion_matrix.png22.33kb
| | ├──bnb_roc_curve.png34.49kb
| | ├──confusion_matrix.png16.50kb
| | ├──decision_tree_model.py7.76kb
| | ├──decision_tree_text.txt4.61kb
| | ├──decision_tree_viz.png666.91kb
| | ├──dt_confusion_matrix.png17.82kb
| | ├──dt_feature_importance.png31.31kb
| | ├──dt_roc_curve.png38.04kb
| | ├──feature_importance.png31.53kb
| | ├──gender_age_boxplot.png15.10kb
| | ├──gender_distribution.png22.45kb
| | ├──gnb_confusion_matrix.png21.77kb
| | ├──gnb_roc_curve.png33.18kb
| | ├──logistic_regression_model.py8.78kb
| | ├──lr_coefficients.png45.18kb
| | ├──lr_confusion_matrix.png18.77kb
| | ├──lr_feature_importance.png31.12kb
| | ├──lr_roc_curve.png32.77kb
| | ├──mnb_confusion_matrix.png19.88kb
| | ├──mnb_roc_curve.png33.74kb
| | ├──naive_bayes_model.py10.29kb
| | ├──nb_models_comparison_roc.png55.42kb
| | ├──policy_data.xlsx93.93kb
| | ├──policy_test.xlsx25.09kb
| | ├──random_forest_model.py6.47kb
| | ├──README.md2.95kb
| | ├──region_correlation.png44.69kb
| | ├──roc_curve.png33.52kb
| | ├──view_data.py0.27kb
| | └──view_excel.py0.22kb
| ├──2-CASE-客户续保预测.pdf2.97M
| ├──1-Cursor数据可视化与洞察.pdf1.01M
| └──笔记20250410.txt6.26kb
├──5-Embeddings和向量数据库
| ├──hotel_recommendation
| | ├──.ipynb_checkpoints
| | ├──.qodo
| | ├──.gitignore0.01kb
| | ├──hotel_rec - nltk.py3.97kb
| | ├──hotel_rec.ipynb142.59kb
| | ├──hotel_rec.py5.55kb
| | └──Seattle_Hotels.csv155.59kb
| ├──word2vec
| | ├──journey_to_the_west
| | ├──models
| | ├──three_kingdoms
| | ├──utils
| | ├──word_seg.py1.11kb
| | └──word_similarity.py1.11kb
| ├──1-Embedding与向量数据库.pdf1.16M
| └──笔记20250414.txt4.19kb
├──6-RAG技术与应用
| ├──CASE-ChatPDF-Faiss
| | ├──.ipynb_checkpoints
| | ├──.qodo
| | ├──faiss-1
| | ├──chatpdf-faiss.ipynb18.85kb
| | ├──chatpdf-faiss.py6.73kb
| | ├──ReadMe.md3.79kb
| | └──浦发上海浦东发展银行西安分行个金客户经理考核办法.pdf323.28kb
| ├──CASE-embedding使用
| | ├──.qodo
| | ├──bge-m3使用.py1.16kb
| | ├──gte-qwen2-使用1.py1.45kb
| | └──gte-qwen2-使用2.py4.66kb
| ├──1-RAG技术与应用.pdf2.07M
| ├──2-NotebookLM使用.pdf1.68M
| └──笔记20250417.txt7.41kb
├──7-RAG高级技术与最佳实践
| ├──Case-ChatPDF-Faiss
| | ├──chatpdf-faiss.ipynb18.24kb
| | ├──chatpdf-faiss.py6.73kb
| | ├──MultiQueryRetriever使用.ipynb5.49kb
| | ├──MultiQueryRetriever使用.py1.30kb
| | └──浦发上海浦东发展银行西安分行个金客户经理考核办法.pdf323.28kb
| ├──CASE-Qwen-Agent-RAG
| | ├──docs
| | ├──qwen-agent-1.ipynb6.35kb
| | ├──qwen-agent-1.py3.28kb
| | ├──qwen-agent-multi-files.ipynb15.72kb
| | ├──qwen-agent-multi-files.py3.84kb
| | └──浦发上海浦东发展银行西安分行个金客户经理考核办法.pdf323.28kb
| ├──graphrag-main
| | └──cases
| ├──rerank
| | ├──beg-reranker.ipynb8.72kb
| | └──beg-reranker.py1.21kb
| ├──1-RAG高级技术与实践.pdf5.33M
| └──笔记20250422.txt6.42kb
├──8-Text2SQL：自助式数据报表开发
| ├──CASE-SQL Copilot
| | ├──insurance
| | ├──codegeex-1.ipynb8.44kb
| | └──qwen-coder1.ipynb6.06kb
| ├──Case-SQL-LangChain
| | ├──.ipynb_checkpoints
| | ├──sql_agent_deepseek.ipynb22.39kb
| | └──sql_life_insurance.ipynb30.58kb
| ├──CASE-SQL-vanna
| | ├──vanna-mysql.ipynb21.86kb
| | └──vanna-mysql.py3.18kb
| ├──SQL数据表源文件
| | ├──agentinfo.sql235.42kb
| | ├──beneficiaryinfo.sql140.62kb
| | ├──claiminfo.sql271.36kb
| | ├──crs_orders.sql4.98kb
| | ├──customerinfo.sql266.22kb
| | ├──employeeinfo.sql303.85kb
| | ├──heros.sql14.66kb
| | ├──policyinfo.sql242.63kb
| | └──productinfo.sql201.10kb
| ├──1-Text2SQL：自助式数据报表开发.pdf3.08M
| ├──2-vanna使用.pdf479.21kb
| └──笔记20250424.txt9.35kb
├──9-LangChain：多任务应用开发
| ├──Case-LangChain使用
| | ├──.ipynb_checkpoints
| | ├──1-LLMChain.ipynb2.73kb
| | ├──2-LLMChain.ipynb7.27kb
| | ├──3-LLMChain.ipynb5.46kb
| | ├──4-ConversationChain.ipynb4.35kb
| | └──5-product_llm.py8.53kb
| ├──CASE-搭建故障诊断Agent
| | ├──2-network_diagnosis_agent.py10.62kb
| | ├──network_diagnosis_agent_logic.md5.46kb
| | └──requirements.txt0.05kb
| ├──CASE-工具链组合
| | ├──1-simple_toolchain.py9.21kb
| | ├──2-simple_toolchain.py7.91kb
| | ├──3-lcel-demo.py1.17kb
| | └──requirements.txt0.11kb
| ├──1-LangChain：多任务应用开发.pdf3.03M
| ├──2-Generative Agents.pdf1.41M
| └──笔记20250429.txt5.20kb
├──常用工具下载
| └──OllamaSetup.exe1001.01M
└──大模型应用开发-资料包.zip260.15M
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zh大模型14期