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Hands On AI Build a RAG Model from Scratch with Open Source

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Source: 1 Logo 1337x
Type: Tutorials
Language: English
Category: Other
Size: 364.3 MB
Added: Oct. 23, 2025, 5:51 p.m.
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Files:
  1. Get Bonus Downloads Here.url 180 bytes
  2. 01 - Introduction to RAG models.mp4 2.5 MB
  3. 01 - Introduction to RAG models.srt 1.3 KB
  4. 01 - Running your LLM from open source.mp4 3.1 MB
  5. 01 - Running your LLM from open source.srt 4.3 KB
  6. 02 - Collecting data to generate our corpus.mp4 2.7 MB
  7. 02 - Collecting data to generate our corpus.srt 3.4 KB
  8. 03 - What are vector embeddings, and how are they generated.mp4 4.8 MB
  9. 03 - What are vector embeddings, and how are they generated.srt 5.6 KB
  10. 04 - Setting up a database and retrieving vectors and files.mp4 5.0 MB
  11. 04 - Setting up a database and retrieving vectors and files.srt 4.8 KB
  12. 05 - Vectorizing a query and finding relevant text.mp4 5.3 MB
  13. 05 - Vectorizing a query and finding relevant text.srt 4.6 KB
  14. 06 - Prompt engineering and packaging pieces together.mp4 4.6 MB
  15. 06 - Prompt engineering and packaging pieces together.srt 5.2 KB
  16. 01 - Setting up a dev container.mp4 15.7 MB
  17. 01 - Setting up a dev container.srt 11.3 KB
  18. 02 - Setting up environment and installing Ollama.mp4 11.7 MB
  19. 02 - Setting up environment and installing Ollama.srt 7.6 KB
  20. 03 - Creating a model file.mp4 18.3 MB
  21. 03 - Creating a model file.srt 11.4 KB
  22. 04 - Running Ollama programmatically through Python.mp4 20.9 MB
  23. 04 - Running Ollama programmatically through Python.srt 9.4 KB
  24. 05 - Generating the corpus.mp4 33.3 MB
  25. 05 - Generating the corpus.srt 14.0 KB
  26. 06 - Extract text from different local file formats with Docling.mp4 15.0 MB
  27. 06 - Extract text from different local file formats with Docling.srt 6.1 KB
  28. 01 - Vector embeddings and their implementation.mp4 5.7 MB
  29. 01 - Vector embeddings and their implementation.srt 7.0 KB
  30. 02 - Setting up your Postgres vector database.mp4 24.1 MB
  31. 02 - Setting up your Postgres vector database.srt 11.0 KB
  32. 03 - Setting up a simple database schema.mp4 23.6 MB
  33. 03 - Setting up a simple database schema.srt 9.6 KB
  34. 04 - Uploading vectors, text, and filenames to the database.mp4 51.2 MB
  35. 04 - Uploading vectors, text, and filenames to the database.srt 23.4 KB
  36. 05 - Retrieving content from your database.mp4 17.4 MB
  37. 05 - Retrieving content from your database.srt 10.0 KB
  38. 01 - Overview of the RAG pipeline.mp4 6.3 MB
  39. 01 - Overview of the RAG pipeline.srt 4.1 KB
  40. 02 - Preparing context, part 1.mp4 19.1 MB
  41. 02 - Preparing context, part 1.srt 9.0 KB
  42. 03 - Preparing context, part 2.mp4 25.9 MB
  43. 03 - Preparing context, part 2.srt 11.0 KB
  44. 04 - Prompt engineering.mp4 20.4 MB
  45. 04 - Prompt engineering.srt 9.6 KB
  46. 05 - Putting it all together to generate a working RAG model.mp4 25.1 MB
  47. 05 - Putting it all together to generate a working RAG model.srt 10.1 KB
  48. 01 - What's next.mp4 2.6 MB
  49. 01 - What's next.srt 1.6 KB
  50. Bonus Resources.txt 70 bytes

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