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Udemy LLM Concepts Deep Dive Conceptual Mastery for Developer

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Files:
  1. Get Bonus Downloads Here.url 180 bytes
  2. 1 -Understanding the Concept of Model.mp4 114.2 MB
  3. 2 -Language Model Tasks and Auto Encoding.mp4 79.0 MB
  4. 3 -Auto Regression and Text Prediction.mp4 121.6 MB
  5. 4 -Text completion.mp4 78.4 MB
  6. 5 -Audience Questions.mp4 127.1 MB
  7. 1 -Pre-training.mp4 144.6 MB
  8. 2 -Instruct tuning.mp4 156.8 MB
  9. 3 -Fine Tuning.mp4 88.1 MB
  10. 4 -Audience Questions.mp4 72.3 MB
  11. 5 -Introduction to Fine-Tuning AI Models.mp4 38.9 MB
  12. 1 -Introduction to Tokens and Embeddings.mp4 71.5 MB
  13. 10 -Audience Questions.mp4 29.3 MB
  14. 2 -Tokenization Explained.mp4 133.5 MB
  15. 3 -Visualizing Tokenization.mp4 26.6 MB
  16. 4 -How token boundaries are formed.mp4 220.3 MB
  17. 5 -How word frequencies are identified.mp4 112.9 MB
  18. 6 -Embeddings and Their Importance.mp4 314.9 MB
  19. 7 -Exploring Embeddings and the N-dimensional space.mp4 116.6 MB
  20. 8 -Embedding Math. Mind-Blowing Examples.mp4 58.0 MB
  21. 9 -Tokenization and Embeddings.mp4 76.5 MB
  22. 1 -Quiz Time Test Your Knowledge.mp4 124.6 MB
  23. 2 -The Concept of Text Similarity.mp4 106.2 MB
  24. 3 -Audience Questions.mp4 71.1 MB
  25. 1 -From Tokens To Text.mp4 151.1 MB
  26. 2 -Introduction to Transformer Architecture.mp4 109.7 MB
  27. 3 -Understanding Attention in LLMs.mp4 137.8 MB
  28. 4 -Addressing Questions on Transformer Architecture.mp4 101.2 MB
  29. 1 -Introduction to Context Length in LLMs.mp4 70.9 MB
  30. 2 -Challenges with Context Limit and Statelessness.mp4 132.9 MB
  31. 1 -Introducing Retrieval Augmented Generation (RAG).mp4 124.0 MB
  32. 2 -Some important terminologies.mp4 68.1 MB
  33. 3 -Vector Databases and Their Role in RAG.mp4 88.6 MB
  34. 4 -How Vector Databases Work.mp4 71.7 MB
  35. 5 -Vector Database Interaction Pseudocode.mp4 32.6 MB
  36. 6 -The RAG Pipeline.mp4 41.1 MB
  37. 7 -Q&A and Final Thoughts.mp4 62.6 MB
  38. Bonus Resources.txt 70 bytes

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