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OverviewWe 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 Full Product DetailsAuthor: Rajaniesh KaushikkPublisher: APress Imprint: APress ISBN: 9798868817205Pages: 451 Publication Date: 01 November 2025 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Not yet available This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release. Table of ContentsChapter 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.ReviewsAuthor InformationRajaniesh Kaushikk didn't just grow into a data and AI leader—he's been building, learning, and teaching since the days when ""cloud"" only meant the weather. During the past 23 years, he has helped global teams harness the power of Generative AI, machine learning, data lakehouse platforms, and Apache Spark to turn complex challenges into scalable, intelligent solutions. He thrives at the intersection of technology, creativity, and community—where ideas are shared, innovations are built, and people grow. Rajaniesh has received Most Valuable Professional awards from both Microsoft and Databricks, along with the distinction of Databricks Champion—honors that reflect his deep commitment to sharing knowledge and driving meaningful impact in the field. He's a sought-after speaker at Microsoft and Databricks, regularly connecting with learners around the globe through his blog at RajanieshKaushikk.com and his YouTube channel @RajanieshKaushikk, where he breaks down complex topics into practical, accessible insights. Outside of technology, Rajaniesh finds joy in cooking, listening to music, and spending time with his wife, daughter, and their ever-curious dog. For Rajaniesh, technology isn't just a profession—it's a means to connect, create, and inspire the next generation of builders. Tab Content 6Author Website:Countries AvailableAll regions |
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