LLMOps in Practice: A Deep Dive

Contents

• Introduction Introduction

  • A deep dive into LLM operations

    53s
  • What are LLMs?

    4m 1s
  • What are transformers?

    3m 42s
  • What is LLMOps?

    8m 52s
• 1. Build a Basic LLM App 1. Build a Basic LLM App

  • Prompting

    7m 26s
  • Advanced prompting

    7m 21s
  • Hosting an app

    3m 16s
  • Create a chatbot

    24m 10s
  • LLM exercise

    3m 33s
  • Adding logging to your server

    9m 31s
• 2. First Steps in Ops 2. First Steps in Ops

  • Coding for logging

    7m 35s
  • Exploring the logging system

    4m 23s
  • RLHF and user feedback

    1m 52s
  • Challenge: Implementing RLHF and user feedback

    2m 35s
  • Demonstrating the ops project completed

    2m 40s
  • Solution: Completing an ops project

    5m 2s
  • Demonstrating the code for the ops

    17m 12s
• 3. BYOD with RAG 3. BYOD with RAG

  • Retrieval augmented generation (RAG)

    8m 14s
  • Installing and setting up a VectorDB

    4m 50s
  • Create a VectorDB

    15m 2s
  • BYOD to a VectorDB

    6m 14s
  • VectorDB: Hands-on use case

    14m 10s
  • Querying the VectorDB

    3m 47s
  • Demonstration: Querying the VectorDB

    11m 33s
  • Extending your app with RAG

    5m 23s
  • RAG: Showing it in action

    9m 48s
  • Challenge: Complete RAG application

    1m 8s
  • Solution: Complete RAG application

    5m 16s
• 4. RAG and Ops 4. RAG and Ops

  • Extending RAG with ops

    2m 9s
  • Logging

    3m 38s
  • Hands-on logging

    10m 23s
  • Metrics

    5m 28s
  • Hands-on metrics

    10m 20s
  • Version management

    4m 50s
  • Hands-on version management

    13m 32s
  • RAG Ops: Updating the data

    4m 37s
  • Hands-on RAG ops

    9m 22s
  • RAG in action: Exercise

    1m 4s
• Conclusion Conclusion

  • Continue your LLMOps learning journey

    1m 56s