RAG

RAG metadata, size 8855.02 MB, 624 files, category video, indexed at 2026-08-07.

大小:8.6 GB 格式:mp4 分类:视频 文件数量:624 个 发掘时间:2026-08-07 19:36:57 最后活跃:2026-08-07 19:36:57

资源标识

Infohashf6c8796b7b92c7183389e3a2f96eaf4419625026 总大小8.6 GB 格式mp4 分类视频 文件数624 发掘时间(北京时间)2026-08-07 19:36:57 最后活跃(北京时间)2026-08-07 19:36:57

下载标识

完整磁力链接 magnet:?xt=urn:btih:f6c8796b7b92c7183389e3a2f96eaf4419625026&dn=RAG
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Tag

文件列表

文件名格式大小
1 - Introduction.htmlhtml544 B
1 -Course Overview (ENG).srtsrt12.1 KB
1 -Course Overview (RUS).srtsrt18.6 KB
1 -Course Overview .mp4mp435.6 MB
2 -Important Tips for the Course (ENG).srtsrt5.7 KB
2 -Important Tips for the Course (RUS).srtsrt9.1 KB
2 -Important Tips for the Course .mp4mp452.2 MB
3 -Explanation of the Links for the Course (ENG).srtsrt2.5 KB
3 -Explanation of the Links for the Course (RUS).srtsrt3.9 KB
3 -Explanation of the Links for the Course .mp4mp49.2 MB
4 - Important Links.htmlhtml6.7 KB
4 -Instructor Introduction Arnold Oberleiter (Arnie) (ENG).srtsrt1.9 KB
4 -Instructor Introduction Arnold Oberleiter (Arnie) (RUS).srtsrt2.8 KB
4 -Instructor Introduction Arnold Oberleiter (Arnie) .mp4mp410.6 MB
4 -Links.pdfpdf32.3 KB
5 -Quick Start with RAG Using Google’s NotebookLM (ENG).srtsrt21.4 KB
5 -Quick Start with RAG Using Google’s NotebookLM (RUS).srtsrt32.0 KB
5 -Quick Start with RAG Using Google’s NotebookLM .mp4mp464.5 MB
1 -What to Expect in This Section (ENG).srtsrt2.3 KB
1 -What to Expect in This Section (RUS).srtsrt3.5 KB
1 -What to Expect in This Section .mp4mp429.3 MB
2 -LLMs Explained ChatGPT, Claude (ENG).srtsrt21.3 KB
2 -LLMs Explained ChatGPT, Claude (RUS).srtsrt30.8 KB
2 -LLMs Explained ChatGPT, Claude, Gemini, Deepseek, Llama, Mistral & More .mp4mp484.2 MB
3 -Function Calling How LLMs Communicate with Tools via APIs (ENG).srtsrt11.9 KB
3 -Function Calling How LLMs Communicate with Tools via APIs (RUS).srtsrt17.7 KB
3 -Function Calling How LLMs Communicate with Tools via APIs and use RAG .mp4mp430.6 MB
4 -Vector Databases, Embedding Models, Tok-K and Chunking for (ENG).srtsrt19.6 KB
4 -Vector Databases, Embedding Models, Tok-K and Chunking for (RUS).srtsrt26.9 KB
4 -Vector Databases, Embedding Models, Tok-K and Chunking for RAG .mp4mp452.2 MB
5 -What is a API (ENG).srtsrt5.1 KB
5 -What is a API (RUS).srtsrt7.7 KB
5 -What is a API .mp4mp425.6 MB
6 -ChatGPT Basics Interface, Models (ENG).srtsrt35.8 KB
6 -ChatGPT Basics Interface, Models (RUS).srtsrt53.1 KB
6 -ChatGPT Basics Interface, Models, Settings, GPTs and the OpenAI Playground .mp4mp489.7 MB
7 -Test Time Compute Explained (ENG).srtsrt6.4 KB
7 -Test Time Compute Explained (RUS).srtsrt9.4 KB
7 -Test Time Compute Explained Thinking Models like Deepseek R1 & OpenAI o3 & o4.mp4mp428.7 MB
8 -Recap of RAG, Vectordatabases, Top-K (ENG).srtsrt4.6 KB
8 -Recap of RAG, Vectordatabases, Top-K (RUS).srtsrt7.6 KB
8 -Recap of RAG, Vectordatabases, Top-K, Chunking, LLMs, Function Calling & APIs.mp4mp455.7 MB
1 -What You’ll Learn in This Section about RAG and GPTs (ENG).srtsrt2.1 KB
1 -What You’ll Learn in This Section about RAG and GPTs (RUS).srtsrt3.1 KB
1 -What You’ll Learn in This Section about RAG and GPTs .mp4mp426.3 MB
2 -First RAG Bot from PDFs with GPTs Data Preparation (Markdown) & System Prompts (ENG).srtsrt29.6 KB
2 -First RAG Bot from PDFs with GPTs Data Preparation (Markdown) & System Prompts (RUS).srtsrt44.2 KB
2 -First RAG Bot from PDFs with GPTs Data Preparation (Markdown) & System Prompts .mp4mp499.6 MB
2 -Systemprompt.docxdocx15.2 KB
3 -Transforming an HTML Webpage into a RAG Chatbot (ENG).srtsrt11.7 KB

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