The Big Book of MLOps: Second Edition

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.

This updated edition will share how building your AI foundation on top
of your data platform makes for robust governance and lineage for
your data and AI assets. We’ll also dive deeper into architectures for
deploying and managing large language models — known as LLMOps.

In this eBook, you’ll learn:

        – 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 a

        – How to monitor data and models through the complete AI lifecycle

        – Best practices to guide your MLOps planning and decision-making