{"product_id":"data-science-solutions-on-azure-the-rise-of-generative-ai-and-applied-ai-9798868809132","title":"Data Science Solutions on Azure: The Rise of Generative AI and Applied AI","description":"\u003cp\u003eThis 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.\u003c\/p\u003e \u003cp\u003eBased 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.\u003c\/p\u003e \u003cp\u003eWritten with a view on how to implement Generative AI in software, this book contains examples and sample code.\u003c\/p\u003e \u003cp\u003eIn 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.\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003e\u003cstrong\u003eWhat's New in this Book\u003c\/strong\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eProvides new concepts, tools, and technologies such as Large and Small Language Models, Semantic Kernel, and Automatic Function Calling\u003c\/li\u003e \u003cli\u003eTakes a deeper dive into using Azure AI Studio for RAG and Prompt Engineering design\u003c\/li\u003e \u003cli\u003eIncludes new and updated case studies for Azure OpenAI\u003c\/li\u003e \u003cli\u003eTeaches about Copilots, plugins, and agents\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003e\u003cstrong\u003eWhat You'll Learn\u003c\/strong\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eGet up to date on the important technical aspects of Large Language Models, based on Azure OpenAI as the reference platform\u003c\/li\u003e \u003cli\u003eKnow about the different types of models: GPT3.5 Turbo, GPT4, GPT4o, Codex, DALL-E, and Small Language Models such as Phi-3\u003c\/li\u003e \u003cli\u003eDevelop new skills such as Prompt Engineering and fine tuning of Large\/Small Language Models\u003c\/li\u003e \u003cli\u003eUnderstand and implement new architectures such as RAG and Automatic Function Calling\u003c\/li\u003e \u003cli\u003eUnderstand approaches for implementing Generative AI using LangChain and Semantic Kernel\u003c\/li\u003e \u003cli\u003eSee how real-world projects help you identify great candidates for Applied AI projects, including Large\/Small Language Models\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003e\u003cstrong\u003eWho This Book Is For\u003c\/strong\u003e\u003c\/p\u003e \u003cp\u003eSoftware engineers and architects looking to deploy end-to-end Generative AI solutions on Azure with the latest tools and techniques.\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cstrong\u003eJulian Soh\u003c\/strong\u003e is a software engineer and a cloud architect with Microsoft, focusing in the areas of artificial intelligence and advanced analytics for independent software vendors\u003cbr\u003e (ISVs) who develop software solutions based on the Microsoft technology stack. Prior to his current role, Julian worked extensively in major public cloud initiatives, such as\u003cbr\u003e SaaS (Microsoft 365), IaaS\/PaaS (Microsoft Azure), and hybrid private-public cloud implementations.\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003e\u003cstrong\u003ePriyanshi Singh\u003c\/strong\u003e is a senior artificial intelligence and machine learning technical specialist at Microsoft, specializing in designing end-to-end cloud solutions that leverage generative AI models and AI implementation best practices. She holds a master's degree in data science from New York University and has a robust background as a data scientist, focusing on machine learning techniques for predictive analytics, computer vision, and natural language processing. Priyanshi is dedicated to helping the public\u003cbr\u003e sector and independent software vendors (ISVs) transform citizen services through artificial intelligence. She has been recognized as Microsoft's FY24 State and Local\u003cbr\u003e Government Pinnacle Winner for her exceptional contributions to AI adoption and the growth of Azure business. Additionally, Priyanshi is a sports enthusiast, excelling in\u003cbr\u003e badminton and enjoying golf and billiards.\u003c\/p\u003e\u003cbr\u003e","brand":"Apress","offers":[{"title":"Default Title","offer_id":50912054018322,"sku":"9798868809132","price":43.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_dda02964-b50e-4463-b409-065c3ac3b47b.jpg?v=1738764459","url":"https:\/\/surprise-castle.myshopify.com\/products\/data-science-solutions-on-azure-the-rise-of-generative-ai-and-applied-ai-9798868809132","provider":"Surprise Castle","version":"1.0","type":"link"}