Data Science Solutions on Azure

This revamped and updated book focuses on the latest in AI technology-Generative AI. It builds on the first edition by moving away from traditional data science into the area of applied AI using the latest breakthroughs in Generative AI.

Based on real-world projects, this edition takes a deep look into new concepts and approaches such as Prompt Engineering, testing and grounding of Large Language Models, and implementing new solution architectures such as the Retrieval Augmented Generation (RAG) in machine learning. You will learn about new embedded AI technologies in Search, such as Semantic and Vector Search.

Written with a view on how to implement Generative AI in software, this book contains examples and sample code.

In addition to traditional Data Science experimentation in Azure Machine Learning (AML) that was covered in the first edition, the authors have extended the use of AML to test and experiment with Large Language Models.

What's New in this Book

• Provides updated data sources and technologies, such as OneLake and Microsoft Fabric. Includes an in-depth look at Retrieval Augmented Generation (RAG) in search technology. Semantic and Vector Search have been added.
• Takes a deeper dive into using AML for RAG and Prompt Engineering
• Includes new and updated case studies  for Azure OpenAI
• Teaches about Copilots and plugins

What You'll Learn

• Get up to date on the important technical aspects of Large Language Models, based on Azure OpenAI as the reference platform
• Know about the different types of models: GPT3.5 Turbo, GPT4, GPT4o, Codex, DALL-E, and Small Language Models
• Develop new skills such as Prompt Engineering and fine tuning of Large Language Models
• Understand and implement new architectures such as RAG
• Understand approaches for implementing Generative AI using LangChain and Semantic Kernel
• See how real-world projects help you identify great candidates for Applied AI projects, including Large Language Models

Who This Book Is For

Software engineers and architects looking to deploy end-to-end Generative AI solutions on Azure with the latest tools and techniques.