Build innovative, scalable, and ethical AI solutions by harnessing the full potential of generative AI with this exhaustive guide Key Features Explore the capabilities of Azure OpenAI’s LLMs Craft end-to-end applications by utilizing the synergy of Azure OpenAI and Cognitive Services Design enterprise-grade GenAI solutions with effective prompt engineering, fine-tuning, and AI safety measures Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionFind out what makes Azure OpenAI a robust platform for building AI-driven solutions that can transform how businesses operate. Written by seasoned experts from Microsoft, this book will guide you in understanding Azure OpenAI from fundamentals through to advanced concepts and best practices. The book begins with an introduction to large language models (LLMs) and the Azure OpenAI Service, detailing how to access, use, and optimize its models. You'll learn how to design and implement AI-driven solutions, such as question-answering systems, contact center analytics, and GPT-powered search applications. Additionally, the chapters walk you through advanced concepts, including embeddings, fine-tuning models, prompt engineering, and building custom AI applications using LangChain and Semantic Kernel. You'll explore real-world use cases such as QnA systems, document summarizers, and SQLGPT for database querying, as well as gain insights into securing and operationalizing these solutions in enterprises. By the end of this book, you'll be ready to design, develop, and deploy scalable AI solutions, ensuring business success through intelligent automation and data-driven insights.What you will learn Understand the concept of large language models and their capabilities Interact with different models in Azure OpenAI using APIs or web interfaces Use content filters and mitigations to prevent harmful content generation Develop solutions with Azure OpenAI for content generation, summarization, semantic search, NLU, code and image generation and analysis Integrate Azure OpenAI with other Azure Cognitive services for enhanced functionality Apply best practices for data privacy, security, and prompt engineering with Azure OpenAI Who this book is forThis book is for software developers, data scientists, AI engineers, ML engineers, system architects, LLM engineers, IT professionals, product managers, and business professionals who want to learn how to use Azure OpenAI to create innovative solutions with generative AI. To fully benefit from this book, you must have both an Azure subscription and Azure OpenAI access, along with knowledge of Python.
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Table of Contents
  1. Introduction to Large Language Models
  2. Azure OpenAI Fundamentals
  3. Azure OpenAI Advanced Topics
  4. Developing an Enterprise Document Question-Answer Solution
  5. Building Contact Center Analytics
  6. Querying from a Structured Database
  7. Code Generation and Documentation
  8. Creating a Basic Recommender Solution with Azure OpenAI
  9. Transforming Text to Video
  10. Creating a Multimodal Multi-Agent Framework with the Azure OpenAI Assistant API
  11. Privacy and Security
  12. Operationalizing Azure OpenAI
  13. Advanced Prompt Engineering
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Produktdetaljer

ISBN
9781805125068
Publisert
2025-02-27
Utgiver
Vendor
Packt Publishing Limited
Høyde
235 mm
Bredde
191 mm
Aldersnivå
01, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
368

Foreword by

Biografisk notat

Amit Mukherjee, a GenAI Technical Specialist at Microsoft, applies AI to revolutionize healthcare by enhancing patient care and driving innovation. With expertise in data & AI, he designs systems that empower data-driven decisions and leads teams in creating generative AI solutions tailored for the healthcare industry. Adithya Saladi is a Software Engineer on Microsoft's Azure Reliability team, has over eight years of experience in building scalable software solutions. He collaborates across teams to deliver innovative, business-critical applications. Adithya also founded GreenOccasion, a non-profit focused on reducing carbon emissions through technology.