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19:00 - Embeddings and Vectors
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Classroom Contents
RAG Crash Course for Beginners
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- 1 00:00 - Introduction to RAG Tutorial
- 2 01:15 - Simplest RAG Explanation
- 3 03:32 - When not to RAG?
- 4 07:40 - What is RAG?
- 5 11:49 - Free Lab 1: Keyword Search TF-IDF & BM25
- 6 15:02 - What are Semantic Search?
- 7 16:54 - Understanding Embedding Models
- 8 19:00 - Embeddings and Vectors
- 9 21:00 - The Dot Product
- 10 26:00 - Lab 2: Embedding Models
- 11 29:50 - Vector Databases Explained
- 12 33:04 - ChromaDB Tutorial
- 13 34:45 - Lab 3: Vector Databases
- 14 38:17 - Chunking Explained
- 15 39:39 - Document Chunking Strategies
- 16 43:22 - Lab 4: Document Chunking
- 17 48:45 - Build your RAG Architecture
- 18 49:31 - Lab 5: Complete RAG Pipeline
- 19 51:50 - Caching, Monitoring and Error Handling
- 20 56:34 - RAG in Production
- 21 68:08 - Conclusion
