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Data Science Solutions on Azure The Rise of Generative AI and Applied AI

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Beschreibung

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...

Beschreibung

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, fine tuning, and implementing new solution architectures such as Retrieval Augmented Generation (RAG). 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 cover new tools such as Azure AI Studio, specifically for testing and experimentation with Generative AI models.


 


What's New in this Book



  • Provides new concepts, tools, and technologies such as Large and Small Language Models, Semantic Kernel, and Automatic Function Calling

  • Takes a deeper dive into using Azure AI Studio for RAG and Prompt Engineering design

  • Includes new and updated case studies  for Azure OpenAI

  • Teaches about Copilots, plugins, and agents


 


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 such as Phi-3

  • Develop new skills such as Prompt Engineering and fine tuning of Large/Small Language Models

  • Understand and implement new architectures such as RAG and Automatic Function Calling

  • 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/Small 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.


 


 

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

19.11.2024

Abbildungen

XIII, 289 p. 258 illus.

Verlag Apress

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

19.11.2024

Abbildungen

XIII, 289 p. 258 illus.

Verlag Apress
Seitenzahl

289

Maße (L/B/H)

25,4/17,8/1,7 cm

Gewicht

576 g

Auflage

2. Auflage

Sprache

Englisch

EAN

9798868809132

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: ProductSafety@springernature.com

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  • Produktbild: Data Science Solutions on Azure
  • Produktbild: Data Science Solutions on Azure

  • Chapter 1: Introduction and Update of AI in the Modern Enterprise.- Chapter 2: Generative AI and Large Language Models.- Chapter 3: Deploy and Explore Azure OpenAI.- Chapter 4: Designing a Generative AI Solution.- Chapter 5: Implementing a Generative AI Solution.- Chapter 6: Prompt Engineering Techniques, Small Language Models, and Fine Tuning.- Chapter 7: Semantic Kernel.- Chapter 8: Structured Data, Codex, Agents, and DBCopilot.- Chapter 9: Azure AI Services.