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.

Pass Azure Fundamentals AZ-900 Exam AZ-900 is an essential exam covering all the foundational concepts about the cloud and Microsoft Azure offerings. Azure fundamentals is a series of below 6 study areas to familiarize you with Azure and its many services and features. Describe Cloud Concepts Describe Core Azure Services Describe Core Solutions and Management Tools Describe General Security and Network Security Describe Identity, Governance, Privacy and Compliance Describe Azure cost management and Service Level Agreements By learning all of these concepts using this guide and practice sets, the reader will be ready to take the exam with confidence. Practice sample tests are in this book. You can also access the most updated versions of the sample sets via an online channel. You can prepare within 5 days or more precisely in less than 24 hours. Learn the fundamentals of Azure, and get AZ-900 certified, with this beginner's guide together with practice sets!

Highlights Packed with useful advice and practical insights to help you bypass typical obstacles and get started efficiently with implementing an Azure Cloud environment. Offers extensive understanding on all Azure cloud-related aspects, from the initial stages to ongoing management, making your journey smoother. Discusses a wide range of topics, from creating an effective strategy to long-term Azure cloud governance. Book Description This book is an in-depth guide on cloud adoption, specifically focusing on the Microsoft Azure platform. It presents a step-by-step approach for businesses looking to commence on their digital transformation journey by leveraging Azure's capabilities. Designed to help organizations understand and apply the Cloud Adoption Framework (CAF), it discusses the strategic aspects of cloud adoption, from business case formulation to planning and execution. The book kicks off with a detailed overview of the CAF, its key components, and how it aligns with your organization's business strategy. Then, it navigates through the various stages of the CAF process, including the Strategy, Plan, Ready, and Adopt phases, providing essential insights into the complexities involved in each step. It further delves into technical aspects, discussing the configuration of Azure environments, cloud operations management, and the critical role of security and compliance in a cloud-based infrastructure. This guide also highlights cost management strategies, showcasing how Azure's flexible pricing models can lead to significant savings over time. It demonstrates the power of automation in managing cloud operations and the potential benefits of Infrastructure as Code (IaC) methodologies. What sets this book apart is its focus on practical implementation, filled with real-world examples, best practices, and common pitfalls to avoid. The approach is both comprehensive and modular, catering to readers new to Azure as well as those with experience in the cloud domain. By the end of this guide, you'll have a clear understanding of how to implement and manage an Azure environment that aligns with your organization's needs, thus facilitating a successful cloud migration and ongoing digital transformation. Whether you're a business leader, IT professional, or simply an enthusiast looking to understand the complexities of cloud adoption, this book serves as a reliable resource, providing a solid foundation in Azure cloud adoption as per the CAF guidelines. Table of Contents Introduction to Cloud Adoption Framework (CAF): This chapter introduces the readers to the concept of the Cloud Adoption Framework, its importance, and the various stages involved in the process. Strategize and Plan: It guides you through the process of establishing key performance indicators (KPIs), assessing your digital estate, and formulating a cloud adoption plan. Ready Phase: Here, we discuss the readiness aspect of cloud adoption. This includes preparing the digital environment, capacity planning, and establishing a cloud adoption team. Adopt Phase: It covers topics like infrastructure setup, data migration, application innovation, and provides guidance on managing possible challenges. Govern and Manage: It offers detailed insights on cost management, security and compliance, and how to establish a robust monitoring and incident response system. Secure and Organize Phase: . It includes security considerations, aligning your organization and teams, and understanding the importance of Azure landing zones. Implementing Best Practices: The final chapter shares the 11 best practices for implementing the Cloud Adoption Framework.

Overcome data mesh adoption challenges using the cloud-scale analytics framework and make your data analytics landscape agile and efficient by using standard architecture patterns for diverse analytical workloads Key Features Delve into core data mesh concepts and apply them to real-world situations Safely reassess and redesign your framework for seamless data mesh integration Conquer practical challenges, from domain organization to building data contracts Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDecentralizing data and centralizing governance are practical, scalable, and modern approaches to data analytics. However, implementing a data mesh can feel like changing the engine of a moving car. Most organizations struggle to start and get caught up in the concept of data domains, spending months trying to organize domains. This is where Engineering Data Mesh in Azure Cloud can help. The book starts by assessing your existing framework before helping you architect a practical design. As you progress, you’ll focus on the Microsoft Cloud Adoption Framework for Azure and the cloud-scale analytics framework, which will help you quickly set up a landing zone for your data mesh in the cloud. The book also resolves common challenges related to the adoption and implementation of a data mesh faced by real customers. It touches on the concepts of data contracts and helps you build practical data contracts that work for your organization. The last part of the book covers some common architecture patterns used for modern analytics frameworks such as artificial intelligence (AI). By the end of this book, you’ll be able to transform existing analytics frameworks into a streamlined data mesh using Microsoft Azure, thereby navigating challenges and implementing advanced architecture patterns for modern analytics workloads.What you will learn Build a strategy to implement a data mesh in Azure Cloud Plan your data mesh journey to build a collaborative analytics platform Address challenges in designing, building, and managing data contracts Get to grips with monitoring and governing a data mesh Understand how to build a self-service portal for analytics Design and implement a secure data mesh architecture Resolve practical challenges related to data mesh adoption Who this book is for This book is for chief data officers and data architects of large and medium-size organizations who are struggling to maintain silos of data and analytics projects. Data architects and data engineers looking to understand data mesh and how it can help their organizations democratize data and analytics will also benefit from this book. Prior knowledge of managing centralized analytical systems, as well as experience with building data lakes, data warehouses, data pipelines, data integrations, and transformations is needed to get the most out of this book.

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.

Unleash the full potential of Power BI with the integration of AI and machine learning techniques using OpenAI Purchase of the print or Kindle book includes a free PDF eBook Key Features Take flight with Power BI machine learning and OpenAI using hands-on examples from the FAA airline data Unlock the full potential of Power BI for advanced analytics using OpenAI Design stunning data presentations, seamless integration of machine learning tools and technologies with OpenAI Book Description Microsoft Power BI is the ultimate solution for businesses looking to make data-driven decisions and unlock the full potential of their data. Unleashing Your Data with Power BI Machine Learning and OpenAI is designed for data scientists and BI professionals seeking to improve their existing solutions and workloads using AI. The book explains the intricacies of the subject by using a workshop-style data story for data ingestion, data modeling, analytics, and predictive analytics with Power BI machine learning. Along the way, you'll learn about AI features, AI visuals, R/Python integration, and OpenAI integration. The workshop-style content allows you to practice all your learnings in real-life challenges and gain hands-on experience. Additionally, you'll gain an understanding of AI/ML, step by step, with replicable examples and references. From enhancing data visualizations to building SaaS Power BI ML models, and integrating Azure OpenAI, this book will help you unlock new capabilities in Power BI. By the end of this book, you'll be well-equipped to build ML models in Power BI, plan projects for both BI and ML, understand R/Python visuals with Power BI, and introduce OpenAI to enhance your analytics solutions. What you will learn Discover best practices for implementing AI and ML capabilities in Power BI along with integration of OpenAI into the solution Understand how to integrate OpenAI and cognitive services into Power BI Explore how to build a SaaS auto ML model within Power BI Gain an understanding of R/Python integration with Power BI Enhance data visualizations for ML feature discovery Discover how to improve existing solutions and workloads using AI and ML capabilities in Power BI with OpenAI Acquire tips and tricks for successfully using AI and ML capabilities in Power BI along with integration of OpenAI into the solution Who this book is for This book is for data science and BI professionals looking to expand their skill sets into Power BI machine learning and OpenAI. This book is also useful for data scientists, data analysts, and IT professionals who want to learn how to incorporate OpenAI into Power BI for advanced experience.

Mastering Microsoft Azure for AI: A Beginner's Guide is the definitive guide for anyone who wants to learn how to build and deploy artificial intelligence (AI) solutions on Microsoft Azure. This comprehensive book covers everything you need to know, from the basics of AI to the latest Azure AI services and technologies. Learn the fundamentals of AI Explore Azure AI services and technologies Build and deploy your own AI solutions Whether you're a beginner or an experienced developer, Mastering Microsoft Azure for AI: A Beginner's Guide is the perfect resource for learning how to build and deploy AI solutions on Microsoft Azure.

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

How do you deal with the problems you face when using Azure? This practical guide provides over 75 recipes to help you to work with common Azure issues in everyday scenarios. That includes key tasks like setting up permissions for a storage account, working with Cosmos DB APIs, managing Azure role-based access control, governing your Azure subscriptions using Azure Policy, and much more. Author Reza Salehi has assembled real-world recipes that enable you to grasp key Azure services and concepts quickly. Each recipe includes CLI scripts that you can execute in your own Azure account. Recipes also explain the approach and provide meaningful context. The solutions in this cookbook will take you beyond theory and help you understand Azure services in practice. You'll find recipes that let you: Store data in an Azure storage account or in a data lake Work with relational and nonrelational databases in Azure Manage role-based access control (RBAC) for Azure resources Safeguard secrets in Azure Key Vault Govern your Azure subscription using Azure Policy Use CLI code to construct your application or fix a particular problem

Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering how you can use deep learning models in your software applications with Microsoft Cognitive Toolkit Key FeaturesUnderstand the fundamentals of Microsoft Cognitive Toolkit and set up the development environment Train different types of neural networks using Cognitive Toolkit and deploy it to productionEvaluate the performance of your models and improve your deep learning skillsBook Description Cognitive Toolkit is a very popular and recently open sourced deep learning toolkit by Microsoft. Cognitive Toolkit is used to train fast and effective deep learning models. This book will be a quick introduction to using Cognitive Toolkit and will teach you how to train and validate different types of neural networks, such as convolutional and recurrent neural networks. This book will help you understand the basics of deep learning. You will learn how to use Microsoft Cognitive Toolkit to build deep learning models and discover what makes this framework unique so that you know when to use it. This book will be a quick, no-nonsense introduction to the library and will teach you how to train different types of neural networks, such as convolutional neural networks, recurrent neural networks, autoencoders, and more, using Cognitive Toolkit. Then we will look at two scenarios in which deep learning can be used to enhance human capabilities. The book will also demonstrate how to evaluate your models' performance to ensure it trains and runs smoothly and gives you the most accurate results. Finally, you will get a short overview of how Cognitive Toolkit fits in to a DevOps environment What you will learnSet up your deep learning environment for the Cognitive Toolkit on Windows and LinuxPre-process and feed your data into neural networksUse neural networks to make effcient predictions and recommendationsTrain and deploy effcient neural networks such as CNN and RNNDetect problems in your neural network using TensorBoardIntegrate Cognitive Toolkit with Azure ML Services for effective deep learningWho this book is for Data Scientists, Machine learning developers, AI developers who wish to train and deploy effective deep learning models using Microsoft CNTK will find this book to be useful. Readers need to have experience in Python or similar object-oriented language like C# or Java.