Azure OpenAI Essentials : A Practical Guide to Unlocking Generative AI-Powered Innovation with Azure OpenAI / Amit Mukherjee, Adithya Saladi, and Marco Casalaina.

Format:

Book

Author/Creator:

Mukherjee, A. (Amit), author.

Saladi, Adithya, author.

Casalaina, Marco, author.

Language:

English

Subjects (All):

Cloud computing.

Microsoft Azure (Computing platform).

Open source software.

Physical Description:

1 online resource (368 pages)

Edition:

First edition.

Place of Publication:

Birmingham, England : Packt Publishing Ltd., [2025]

Biography/History:

Mukherjee Amit: 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. Saladi Adithya: 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.

Summary:

Build innovative, scalable, and ethical AI solutions by harnessing the full potential of generative AI with this exhaustive guideKey FeaturesExplore the capabilities of Azure OpenAI’s LLMsCraft end-to-end applications by utilizing the synergy of Azure OpenAI and Cognitive ServicesDesign enterprise-grade GenAI solutions with effective prompt engineering, fine-tuning, and AI safety measuresPurchase of the print or Kindle book includes a free PDF eBookBook 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 learnUnderstand the concept of large language models and their capabilitiesInteract with different models in Azure OpenAI using APIs or web interfacesUse content filters and mitigations to prevent harmful content generationDevelop solutions with Azure OpenAI for content generation, summarization, semantic search, NLU, code and image generation and analysisIntegrate Azure OpenAI with other Azure Cognitive services for enhanced functionalityApply best practices for data privacy, security, and prompt engineering with Azure OpenAIWho 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.

Contents:

Azure OpenAI Essentials: A practical guide to unlocking generative AI-powered innovation with Azure OpenAI

Notes:

Includes bibliographical references and index.

Description based on publisher supplied metadata and other sources.

Description based on print version record.

ISBN:

1-80512-265-7