Data-centric MLOps and LLMOps

Report Cover
Discover the latest strategies for deploying generative AI and machine learning models efficiently. The Big Book of MLOps covers how to collaborate on a common platform using powerful, open frameworks such as Delta Lake for data pipelines, MLflow for model management (including LLMs) and Databricks Workflows for automation.

Report Snapshot

  • The essential components of an MLOps reference architecture
  • How to apply retrieval augmented generation (RAG) to enhance language models for more informed and accurate responses
  • How to leverage a data-centric platform to securely move AI assets into production and govern them
  • How to monitor data and models through the complete AI lifecycle
  • Best practices to guide your MLOps planning and decision-making

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