Large Language Models - Application through Production

Large Language Models - Application through Production

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LLM Module 5: Society and LLMs | 5.2 Module Overview

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LLM Module 5: Society and LLMs | 5.2 Module Overview

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Large Language Models - Application through Production

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  1. 1 LLM Module 2 - Embeddings, Vector Databases, and Search | 2.6 Best Practices
  2. 2 LLM Module 2 - Embeddings, Vector Databases, and Search | 2.7 Summary
  3. 3 LLM Module 2 - Embeddings, Vector Databases, and Search | 2.8.1 Notebook Demo Part 1
  4. 4 LLM Module 2 - Embeddings, Vector Databases, and Search | 2.8.2 Notebook Demo Part 2
  5. 5 LLM Module 2 - Embeddings, Vector Databases, and Search | 2.9 Notebook Demo Pinecone (Optional)
  6. 6 LLM Module 2 - Embeddings, Vector Databases, and Search | 2.10 Notebook Demo Weaviate (Optional)
  7. 7 LLM Module 3 - Multi-stage Reasoning | 3.1 Introduction
  8. 8 LLM Module 3 - Multi-stage Reasoning | 3.2 Module Overview
  9. 9 LLM Module 3 - Multi-stage Reasoning | 3.3 Prompt Engineering
  10. 10 LLM Module 3 - Multi-stage Reasoning | 3.4 LLM Chains
  11. 11 LLM Module 3 - Multi-stage Reasoning | 3.5 Agents
  12. 12 LLM Module 3 - Multi-stage Reasoning | 3.6 Summary
  13. 13 LLM Module 3 - Multi-stage Reasoning | 3.7.1 Notebook Demo Part 1
  14. 14 LLM Module 3 - Multi-stage Reasoning | 3.7.2 Notebook Demo Part 2
  15. 15 LLM Module 3 - Multi-stage Reasoning | 3.7.3 Notebook Demo Part 3
  16. 16 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.1 Introduction
  17. 17 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.2 Module Overview
  18. 18 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.3 Applying Foundation LLMs
  19. 19 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.4 Fine Tuning: Few-shot Learning
  20. 20 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.5 Fine Tuning: Instruction-following LLMs
  21. 21 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.6 Fine Tuning: LLMs as a Service
  22. 22 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.7 Fine Tuning: DIY
  23. 23 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.8 Dolly
  24. 24 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.9 Evaluating LLMs
  25. 25 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.10 Task specific Evaluations
  26. 26 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.11 Guest Lecture Harrison Chase, LangChain Creator
  27. 27 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.12 Summary
  28. 28 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.13.1 Notebook Demo Part 1
  29. 29 LLM Module 4: Fine-tuning and Evaluating LLMs | 4.13.2 Notebook Demo Part 2
  30. 30 LLM Module 5: Society and LLMs | 5.1 Introduction
  31. 31 LLM Module 5: Society and LLMs | 5.2 Module Overview
  32. 32 LLM Module 5: Society and LLMs | 5.3 Risks and Limitations
  33. 33 LLM Module 5: Society and LLMs | 5.4 Hallucination
  34. 34 LLM Module 5: Society and LLMs | 5.5 Mitigation Strategies
  35. 35 LLM Module 5: Society and LLMs | 5.6 Summary
  36. 36 LLM Module 5: Society and LLMs | 5.7.1 Notebook Demo Part 1
  37. 37 LLM Module 5: Society and LLMs | 5.7.2 Notebook Demo Part 2
  38. 38 LLM Module 6: LLMOps | 6.1 Introduction
  39. 39 LLM Module 6: LLMOps | 6.2 Module Overview
  40. 40 LLM Module 6: LLMOps | 6.3 Traditional MLOps
  41. 41 LLM Module 6: LLMOps | 6.4 LLMOps
  42. 42 LLM Module 6: LLMOps | 6.5 LLMOps Details
  43. 43 LLM Module 6: LLMOps | 6.6 Summary
  44. 44 LLM Module 6: LLMOps | 6.7 Notebook Demo

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