"Generative AI with Microsoft Azure" is a comprehensive guide that explores the integration of generative artificial intelligence (AI) with Azure's robust platform, highlighting the transformative potential of AI across various industries. The book is structured into five key parts, each delving into different aspects of generative AI and its applications on Azure. **Part I: Introduction to Generative AI and Microsoft Azure** provides a foundational understanding of generative AI, including its definitions, applications, and the different models like GANs, VAEs, and Transformers. It also introduces Microsoft Azure, guiding readers through setting up an Azure account, and exploring Azure AI and machine learning services. **Part II: Generative Models on Azure** dives into the implementation of specific generative models on Azure. It covers setting up and training Generative Adversarial Networks (GANs), building and deploying Variational Autoencoders (VAEs), and implementing advanced language models like GPT and BERT. This section emphasizes the practical steps and Azure tools necessary for working with these models. **Part III: Advanced Topics and Use Cases** explores specialized applications of generative AI, such as image and video generation, natural language generation (NLG), and conversational agents. It showcases real-world use cases and how Azure services, like Cognitive Services and Bot Service, enhance these applications, offering insights into their implementation and impact. **Part IV: Deployment and Scaling** focuses on the practicalities of deploying generative AI models on Azure. It discusses best practices for deployment, the use of Azure Kubernetes Service (AKS) for container orchestration, and techniques for monitoring and managing models. The section also covers strategies for scaling AI solutions effectively using Azure’s infrastructure, with an emphasis on cost management and optimization. **Part V: Case Studies and Future Trends** presents industry-specific case studies demonstrating the application of generative AI in healthcare, finance, and creative industries. It concludes with a forward-looking perspective on emerging technologies, ethical considerations, and the future trajectory of generative AI on Azure, highlighting the importance of responsible AI practices. Overall, "Generative AI with Microsoft Azure" serves as an essential resource for professionals and enthusiasts looking to leverage Azure's capabilities to harness the power of generative AI, offering practical guidance, real-world applications, and insights into future advancements.

Generative AI in the Courtroom: A Practical Handbook for Modern Justice offers a groundbreaking look at how cutting-edge technology can transform the legal system. Co-authored by Aspire K Swaminathan, a serial entrepreneur and doctoral scholar in Generative AI, and Anita Thomas, a seasoned lawyer with over 30 years of practice, this book addresses one of the most pressing challenges in today’s judiciary—efficiency. In a legal ecosystem often bogged down by delays and inefficiencies, this handbook provides a practical roadmap for integrating AI into courtrooms. From enhancing legal research to drafting documents and assisting judges in decision-making, the book explores real-world applications of AI to improve access to justice. It balances technical insight with ethical considerations, offering clear, actionable strategies for legal professionals at every level. Whether you’re a lawyer, judge, policymaker, or simply curious about the future of law, this book provides a glimpse into how technology can modernize the judiciary and bring justice closer to those who need it most."

"Generative AI with Microsoft Azure" is a comprehensive guide that explores the integration of generative artificial intelligence (AI) with Azure's robust platform, highlighting the transformative potential of AI across various industries. The book is structured into five key parts, each delving into different aspects of generative AI and its applications on Azure. **Part I: Introduction to Generative AI and Microsoft Azure** provides a foundational understanding of generative AI, including its definitions, applications, and the different models like GANs, VAEs, and Transformers. It also introduces Microsoft Azure, guiding readers through setting up an Azure account, and exploring Azure AI and machine learning services. **Part II: Generative Models on Azure** dives into the implementation of specific generative models on Azure. It covers setting up and training Generative Adversarial Networks (GANs), building and deploying Variational Autoencoders (VAEs), and implementing advanced language models like GPT and BERT. This section emphasizes the practical steps and Azure tools necessary for working with these models. **Part III: Advanced Topics and Use Cases** explores specialized applications of generative AI, such as image and video generation, natural language generation (NLG), and conversational agents. It showcases real-world use cases and how Azure services, like Cognitive Services and Bot Service, enhance these applications, offering insights into their implementation and impact. **Part IV: Deployment and Scaling** focuses on the practicalities of deploying generative AI models on Azure. It discusses best practices for deployment, the use of Azure Kubernetes Service (AKS) for container orchestration, and techniques for monitoring and managing models. The section also covers strategies for scaling AI solutions effectively using Azure’s infrastructure, with an emphasis on cost management and optimization. **Part V: Case Studies and Future Trends** presents industry-specific case studies demonstrating the application of generative AI in healthcare, finance, and creative industries. It concludes with a forward-looking perspective on emerging technologies, ethical considerations, and the future trajectory of generative AI on Azure, highlighting the importance of responsible AI practices. Overall, "Generative AI with Microsoft Azure" serves as an essential resource for professionals and enthusiasts looking to leverage Azure's capabilities to harness the power of generative AI, offering practical guidance, real-world applications, and insights into future advancements.

Get ready to pass the certification exam on your first attempt by gaining actionable insights into AI concepts, ML techniques, and Azure AI services covered in the latest AI-900 exam syllabus from two industry experts Key Features Discover Azure AI services, including computer vision, Auto ML, NLP, and OpenAI Explore AI use cases, such as image identification, chatbots, and more Work through 145 practice questions under chapter-end self-assessments and mock exams Purchase of this book unlocks access to web-based exam prep resources, including mock exams, flashcards, and exam tips Book Description The AI-900 exam helps you take your first step into an AI-shaped future. Regardless of your technical background, this book will help you test your understanding of the key AI-related topics and tools used to develop AI solutions in Azure cloud. This exam guide focuses on AI workloads, including natural language processing (NLP) and large language models (LLMs). You'll explore Microsoft's responsible AI principles like safety and accountability. Then, you'll cover the basics of machine learning (ML), including classification and deep learning, and learn how to use training and validation datasets with Azure ML. Using Azure AI Vision, face detection, and Video Indexer services, you'll get up to speed with computer vision-related topics like image classification, object detection, and facial detection. Later chapters cover NLP features such as key phrase extraction, sentiment analysis, and speech processing using Azure AI Language, speech, and translator services. The book also guides you through identifying GenAI models and leveraging Azure OpenAI Service for content generation. At the end of each chapter, you'll find chapter review questions with answers, provided as an online resource. By the end of this exam guide, you'll be able to work with AI solutions in Azure and pass the AI-900 exam using the online exam prep resources. What you will learn Discover various types of artificial intelligence (AI)workloads and services in Azure Cover Microsoft's guiding principles for responsible AI development and use Understand the fundamental principles of how AI and machine learning work Explore how AI models can recognize content in images and documents Gain insights into the features and use cases for natural language processing Explore the capabilities of generative AI services Who this book is for Whether you're a cloud engineer, software developer, an aspiring data scientist, or simply interested in learning AI/ML concepts and capabilities on Azure, this book is for you. The book also serves as a foundation for those looking to attempt more advanced AI and data science-related certification exams (e.g. Microsoft Certified: Azure AI Engineer Associate). Although no experience in data science and software engineering is required, basic knowledge of cloud concepts and client-server applications is assumed.

Master core data architecture design concepts and Azure Data & AI services to gain a cloud data and AI architect’s perspective to developing end-to-end solutions Purchase of the print or Kindle book includes a free PDF eBook Key Features Translate and implement conceptual architectures with the right Azure services Inject artificial intelligence into data solutions for advanced analytics Leverage cloud computing and frameworks to drive data science workloads Book DescriptionWith data’s growing importance in businesses, the need for cloud data and AI architects has never been higher. The Azure Data and AI Architect Handbook is designed to assist any data professional or academic looking to advance their cloud data platform designing skills. This book will help you understand all the individual components of an end-to-end data architecture and how to piece them together into a scalable and robust solution. You’ll begin by getting to grips with core data architecture design concepts and Azure Data & AI services, before exploring cloud landing zones and best practices for building up an enterprise-scale data platform from scratch. Next, you’ll take a deep dive into various data domains such as data engineering, business intelligence, data science, and data governance. As you advance, you’ll cover topics ranging from learning different methods of ingesting data into the cloud to designing the right data warehousing solution, managing large-scale data transformations, extracting valuable insights, and learning how to leverage cloud computing to drive advanced analytical workloads. Finally, you’ll discover how to add data governance, compliance, and security to solutions. By the end of this book, you’ll have gained the expertise needed to become a well-rounded Azure Data & AI architect.What you will learn Design scalable and cost-effective cloud data platforms on Microsoft Azure Explore architectural design patterns with various use cases Determine the right data stores and data warehouse solutions Discover best practices for data orchestration and transformation Help end users to visualize data using interactive dashboarding Leverage OpenAI and custom ML models for advanced analytics Manage security, compliance, and governance for the data estate Who this book is forThis book is for anyone looking to elevate their skill set to the level of an architect. Data engineers, data scientists, business intelligence developers, and database administrators who want to learn how to design end-to-end data solutions and get a bird’s-eye view of the entire data platform will find this book useful. Although not required, basic knowledge of databases and data engineering workloads is recommended.

Unveiling the power and potential of Generative AI for a limitless future KEY FEATURES ● Holistic and accessible journey into Generative AI. ● Indispensable guide for unleashing Generative AI potential. ● Transforming technology, business, art, and innovation, covering technological advancements and business optimization. DESCRIPTION The Potential of Generative AI invites you for a captivating journey into the revolutionary technology, where machines become co-creators and the line between imagination and reality blurs. You will learn how AI helps doctors, engineers, and scientists solve real-world problems. Next, you will explore use cases where ChatGPT can boost productivity and enhance creativity. The book explores the journey from the origins of this revolutionary technology to its cutting-edge applications. Discover how generative models like GANs and VAEs work, and familiarize yourself with the impact they are making in fields like healthcare, finance, and art. Through real-world case studies and engaging examples, you will witness AI generating life-saving drugs, composing music, and even designing innovative products. This book explores the cutting-edge capabilities and potential of generative AI in the tech landscape. It will help you discover how generative AI can unlock new opportunities and enhance business operations. WHAT YOU WILL LEARN ● Learn about the different types of generative models, how they work, and their impact across various industries including healthcare, finance, and entertainment. ● Explore the creative potential of generative AI in art, music, and design. ● Develop Generative Adversarial Networks (GANs), with a focus on their architecture, training process, and real-world applications. ● Build and deploy generative models, ensuring readers to leverage this powerful technology. ● Perfect the art of generating text, images, music, and even code with AI, utilize your creative potential. WHO THIS BOOK IS FOR This book is for artists, programmers, musicians, designers, writers, researchers, entrepreneurs, scientists, Machine Learning practitioners and dreamers of all sorts. Generative AI awaits and is ready to transform your craft and empower your vision. TABLE OF CONTENTS 1. Introduction to Generative AI 2. Generative AI in Industries 3. Fundamentals of Generative Models 4. Applications Across Industries 5. Creative Expression with Generative AI 6. Generative AI in Business and Innovation 7. Deep Dive into GANs 8. Building and Deploying Generative Models

Get the details, examples, and best practices you need to build generative AI applications, services, and solutions using the power of Azure OpenAI Service. With this comprehensive guide, Microsoft AI specialist Adrián González Sánchez examines the integration and utilization of Azure OpenAI Service—using powerful generative AI models such as GPT-4 and GPT-4o—within the Microsoft Azure cloud computing platform. To guide you through the technical details of using Azure OpenAI Service, this book shows you how to set up the necessary Azure resources, prepare end-to-end architectures, work with APIs, manage costs and usage, handle data privacy and security, and optimize performance. You'll learn various use cases where Azure OpenAI Service models can be applied, and get valuable insights from some of the most relevant AI and cloud experts. Ideal for software and cloud developers, product managers, architects, and engineers, as well as cloud-enabled data scientists, this book will help you: Learn how to implement cloud native applications with Azure OpenAI Service Deploy, customize, and integrate Azure OpenAI Service with your applications Customize large language models and orchestrate knowledge with company-owned data Use advanced roadmaps to plan your generative AI project Estimate cost and plan generative AI implementations for adopter companies

Develop cloud-native skills by learning Azure cloud infrastructure offerings KEY FEATURES ● Master cloud-native development fundamentals and Azure services. ● Application security, monitoring, and efficient management. ● Explore advanced services like Azure Machine Learning & IoT Hub. DESCRIPTION Azure is a powerful cloud computing platform with a wide range of services. Reading this book can help you gain an in-depth understanding of these services and how to use them effectively. Being one of the most popular cloud computing platforms, having knowledge and skills in Azure can be a valuable asset in your career. Explore Microsoft Azure for cloud-native development. Understand its basics, benefits, and services. Learn about identity management, compute resources, and application building. Discover containerization with Azure Kubernetes Service and Azure Container Registry. Dive into microservices architecture and serverless development with Azure Functions. Understand security, monitoring, logging, and CI/CD pipelines with Azure DevOps. Finally, explore advanced services like Azure Machine Learning and Azure IoT Hub, with real-world case studies and insights into future trends. Azure is constantly evolving, with new features and services being added regularly. Reading books on Azure cloud can help you stay up-to-date with the latest developments in the platform and keep your skills current. WHAT YOU WILL LEARN ● Design and build scalable cloud-native apps. ● Utilize Azure services for identity, compute, and storage. ● Implement containerization for efficient packaging and deployment. ● Secure applications with robust Azure security features. ● Manage and monitor applications for optimal performance and reliability. WHO THIS BOOK IS FOR This book is ideal for software developers, architects, and cloud engineers looking to build and deploy modern, scalable applications on the Microsoft Azure cloud platform. TABLE OF CONTENTS 1. Introduction to cloud and cloud native development 2. Azure Services for Cloud Native Development 3. Data Storage Services on Azure Cloud 4. Azure Kubernetes and Container Registry 5. Developing Applications on Azure 6. Monitoring And Logging Applications on Azure 7. Security and Governance on Azure 8. Deploying Applications on Azure 9. Advance Azure Services 10. Case Studies and best practice 11. Generative AI and Future Trends

Embrace emerging AI trends and integrate your operations with cutting-edge solutions Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like generative AI, ChatGPT, and machine learning (ML) into their suite of cloud-based solutions. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. The author shows you how to start an enterprise-wide AI transformation effort, taking you all the way through to implementation, with clearly defined processes, numerous examples, and hands-on exercises. You’ll also discover best practices on optimizing cloud infrastructure for scalability and automation. Enterprise AI in the Cloud helps you gain a solid understanding of: AI-First Strategy: Adopt a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovation State-of-the-Art Use Cases: Learn from emerging AI/ML use cases, such as ChatGPT, VR/AR, blockchain, metaverse, hyper-automation, generative AI, transformer models, Keras, TensorFlow in the cloud, and quantum machine learning Platform Scalability and MLOps (ML Operations): Select the ideal cloud platform and adopt best practices on optimizing cloud infrastructure for scalability and automation AWS, Azure, Google ML: Understand the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS, and Google Cloud platforms AI-Driven Innovation Excellence: Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture Ethical and Trustworthy AI Mastery: Implement Responsible AI by avoiding common risks while maintaining transparency and ethics Scaling AI Enterprise-Wide: Scale your AI implementation using Strategic Change Management, AI Maturity Models, AI Center of Excellence, and AI Operating Model Whether you're a beginner or an experienced AI or MLOps engineer, business or technology leader, or an AI student or enthusiast, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments. With over 300 review questions, 50 hands-on exercises, templates, and hundreds of best practice tips to guide you through every step of the way, this book is a must-read for anyone seeking to accelerate AI transformation across their enterprise.

Streamline your complex processes and optimize your organization's operational efficiency, cost-effectiveness, and customer experience by unlocking the potential of Microsoft Azure Cognitive Services and OpenAI Purchase of the print or Kindle book includes a free PDF eBook Key Features Minimize costs and maximize operations by automating mundane activities using AI tools Ideate solutions using real-world examples for manufacturing process improvement with AI Master TCO and ROI analysis for implementing AI solutions, automating operations, and ideating innovative manufacturing solutions with real-world examples Book Description Azure Cognitive Services and OpenAI are a set of pre-built artificial intelligence (AI) solution APIs that can be leveraged from existing applications, allowing customers to take advantage of Microsoft's award-winning Vision, Speech, Text, Decision, and GPT-4 AI capabilities. With Practical Guide to Azure Cognitive Services, you'll work through industry-specific examples of implementations to get a head-start in your production journey. You'll begin with an overview of the categorization of Azure Cognitive Services and the benefits of embracing AI solutions for practical business applications. After that, you'll explore the benefits of using Azure Cognitive Services to optimize efficiency and improve predictive capabilities. Then, you'll learn how to leverage Vision capabilities for quality control, Form Recognizer to streamline supply chain nuances, language understanding to improve customer service, and Cognitive Search for next-generation knowledge-mining solutions. By the end of this book, you'll be able to implement various Cognitive Services solutions that will help you enhance efficiency, reduce costs, and improve the customer experience at your organization. You'll also be well equipped to automate mundane tasks by reaping the full potential of OpenAI. What you will learn Master cost-effective deployment of Azure Cognitive Services Develop proven solutions from an architecture and development standpoint Understand how Cognitive Services are deployed and customized Evaluate various uses of Cognitive Services with different mediums Disseminate Azure costs for Cognitive Services workloads smoothly Deploy next-generation Knowledge Mining solutions with Cognitive Search Explore the current and future journey of OpenAI Understand the value proposition of different AI projects Who this book is for This book is for data scientists, technology leaders, and software engineers looking to implement Azure Cognitive Services with the help of sample use cases derived from success stories. Experience with Python as well as an overall understanding of the Azure Portal with related services such as Azure Data Lake Storage and Azure Functions will help you make the most of this book.