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The Data Lakehouse revolution = harn...

Kaushikk, Rajaniesh.

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The Data Lakehouse revolution = harnessing the power of Databricks for generative AI and machine learning /

Record Type:	Electronic resources : Monograph/item
Title/Author:	The Data Lakehouse revolution/ by Rajaniesh Kaushikk ; foreword by Scott Hanselman.
Reminder of title:	harnessing the power of Databricks for generative AI and machine learning /
Author:	Kaushikk, Rajaniesh.
other author:	Hanselman, Scott.
Published:	Berkeley, CA :Apress : : 2025.,
Description:	xxiii, 451 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Microsoft Azure (Computing platform) -
Online resource:	https://doi.org/10.1007/979-8-8688-1721-2
ISBN:	9798868817212

The Data Lakehouse revolution = harnessing the power of Databricks for generative AI and machine learning /
Kaushikk, Rajaniesh.

The Data Lakehouse revolutionharnessing the power of Databricks for generative AI and machine learning /[electronic resource] :by Rajaniesh Kaushikk ; foreword by Scott Hanselman. - Berkeley, CA :Apress :2025. - xxiii, 451 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9798868817212

Standard No.: 10.1007/979-8-8688-1721-2doiSubjects--Topical Terms:

3201298
Microsoft Azure (Computing platform)

LC Class. No.: TK5105.88813

Dewey Class. No.: 006.76

The Data Lakehouse revolution = harnessing the power of Databricks for generative AI and machine learning /
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505 0 $a 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.
520 $a 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.
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