ML and Generative AI in the Data Lakehouse

Machine Learning and Generative AI in the Data Lakehouse is your practical guide to building AI applications at scale. This book is tailored for data scientists and AI practitioners aiming to harness the power of Databricks for deploying scalable ML solutions. It navigates through essential topics like setting up ML environments, managing lifecycles with MLflow, and controlling costs without compromising performance.

What You'll Learn

• How to build and deploy ML and GenAI models on Databricks
• Techniques for extracting insights using large language models in this ML ebook pdf
• Strategies to combine traditional ML with Generative AI for scalable solutions
• Cost management tactics using open-source models
• Best practices for model governance with MLflow and Unity Catalog

Who This Book Is For

This book is ideal for data scientists, AI developers, and IT professionals who aim to implement scalable machine learning and AI solutions using the Databricks platform. It assumes a basic familiarity with AI concepts and some experience with data management.

What You Need to Know First

Readers should have a foundational understanding of machine learning principles and familiarity with data lakehouse architectures. Prior experience with Databricks is advantageous but not required.

Why This Book

Unlike other AI resources, this book offers a comprehensive look at deploying AI models within a lakehouse structure, emphasizing real-world application and governance. It stands out by focusing on both traditional ML and emerging Generative AI techniques.

What's Inside

Authored by Bennie Haelen and published by O'Reilly Media, this 448-page book offers detailed chapters on model deployment, cost management, and the integration of AI technologies within scalable architectures.