The Data Lakehouse Revolution

We are racing toward a new kind of AI—faster, smarter, and more connected than ever. At the heart of it is the Data Lakehouse, and Databricks is the engine powering the transformation. Whether you're a data scientist training models, an engineer scaling pipelines, or an architect modernizing your stack, this book gives you what you need to stay ahead. Inside, you'll understand how to unlock the full potential of Machine Learning and Generative AI (GenAI) using Databricks—no fluff, just real tools, real strategies, and real results. From MLFlow and AutoML to Unity Catalog, Retrieval Augment Generation (RAG), and Vector Search, you'll get a complete blueprint for building intelligent systems that actually work in production. With step-by-step labs, industry case studies, and expert tips from someone who's lived through the entire evolution of enterprise AI, this book is your guide to mastering what's next. If you're serious regarding building AI that matters, this is where your journey begins. What You'll Learn

• Build full-stack ML and GenAI solutions on Databricks
• Train and track models with MLFlow, AutoML, and tuning strategies
• Secure and govern data with Unity Catalog
• Apply explainable, ethical AI techniques
• Deploy and monitor ML models in real-world pipelines
• Use RAG and vector search to power GenAI applications
• Gain confidence with hands-on labs and real enterprise use cases

Who This Book Is For Azure administrators, data architects, and data engineers Chapter 1: Getting Started with Databricks.- Chapter 2: Introduction to Machine Learning and Data Lakehouses.- Chapter 3: Data Preparation and Management.- Chapter 4: Building Machine Learning Models.- Chapter 5: AutoML and Model Optimization.- Chapter 6: Deploying Machine Learning Models.- Chapter 7: Advanced Topics in Machine Learning.- Chapter 8: Lakehouse AI and Retrieval-Augmented Generation (RAG).- Chapter 9: Conclusion and Next Steps.