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Unlock the potential of IoT with Microsoft Azure through this comprehensive guide, designed to elevate your understanding and implementation of cutting-edge IoT network and security solutions. Whether you are a beginner or a seasoned professional, this book offers clear, actionable insights to help you master the intricacies of IoT with Azure. This book equips you with the expertise to design and deploy secure, efficient, and scalable IoT networks using Microsoft Azure. It is your key to becoming a proficient IoT architect and security specialist. What You Will Learn Know the fundamentals of IoT networks and security, including key concepts, terminologies, and the importance of securing IoT deployments Dive into Azure Edge Services to design and deploy edge solutions that bring computation and data storage closer to the data source, enhancing speed and efficiency Explore the architecture and deployment of Azure IoT networks to gain practical knowledge on setting up scalable, reliable, and secure IoT networks tailored to your needs Study best practices and strategies for securing your IoT environment and ensuring robust protection against emerging threats Monitor and manage your IoT solutions effectively via tools and techniques for maintaining optimal performance, diagnosing issues, and ensuring seamless operation of your IoT networks Who This Book Is For IoT network and security engineers, architects, and Azure IoT developers.

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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 .

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Break the vicious circle of designs perpetuating the errors of the past and “just click next and accept the defaults” implementations preventing a secure and reliable future. This book looks at the typical patterns and antipatterns in Active Directory (AD) design, deployment, and operations and provides an approach to building and operating AD that is based on engineering (analyzing and fulfilling requirements) rather than design (formulating requirements). The book starts with an historical overview of AD and its future 25 years later. You then learn about the challenges that organizations running AD are facing today followed by understanding how to avoid them while learning modern requirements for more efficient and effective AD performance. After that, you go through business requirements influencing the AD topology along with ways to engineer information lookup to protect high-value objects. The book looks at two main protocols and the many dialects that AD offers to engineer an authentication service that fulfills modern requirements while leaving insecure legacy configurations behind. Managing AD from both the security and usability perspectives is discussed next in the book. Building, operating, and transitioning to a modern AD is demonstrated in detail. The book guides you with the next steps of your journey to achieve a secure and reliable AD. After reading this book, you will be able to bridge the gap between the two approaches by analyzing real-world business requirements, explaining the decision-making process in both design and engineering, and ultimately providing concrete engineering guidelines for typical implementation scenarios. What Will You Learn Build a modern Active Directory (AD), leaving behind design antipatterns that are not valid anymore Build a “secure by design” AD and accommodate legacy technology without compromising the overall security Understand advanced AD functionality such as controlling object visibility and partitioning Kerberos authentication by Authentication Policies Operate a modern AD, react to changing business requirements, and respond to ever-evolving security threats .

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Microsoft Project.

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