Data-centric MLOps and LLMOps
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