Search results for ""Author Abhishek Mishra""

Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services. Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You’ll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you’ll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems. • Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building • Discover common neural network frameworks with Amazon SageMaker • Solve computer vision problems with Amazon Rekognition • Benefit from illustrations, source code examples, and sidebars in each chapter The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem.

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Learn Azure-based features to build and deploy Java applications on Microsoft’s Azure cloud platform. This book provides examples of components on Azure that are of special interest to Java programmers, including the different deployment models that are available. The book shows how to deploy your Java applications in Azure WebApp, Azure Kubernetes Service, Azure Functions, and Azure Spring Cloud. Also covered is integration with components such as Graph API, Azure Storage, Azure Redis Cache, and Azure SQL. The book begins with a brief discussion of cloud computing and an introduction to Java support on Azure. You’ll then learn how to deploy Java applications using each of the deployment models, and you’ll see examples of integrating with Azure services that are of particular interest to Java programmers. Security is an important aspect, and this book shows you how to enable authentication and authorization for your Java applications using Azure Active Directory. Implementing a DevOps strategy is essential in today’s market when building any application. Examples in this book show you how to build continuous integration and continuous deployment pipelines to build and deploy Java applications on Azure. The book focuses on the best practices you should follow while designing and implementing Java applications on Azure. The book also elaborates on monitoring and debugging Java applications running on Azure using Application Insights and Azure Monitor. What You Will Learn Design and build Azure-based Java applications Run Azure-based Java applications on services such as Azure App Services, Azure Spring Cloud, Azure Functions, and Azure Kubernetes Service Integrate Azure services such as Azure SQL, Azure Storage Account, Azure Redis Cache, Azure Active Directory, and more with Java applications running on Azure Monitor and debug Java applications running on Azure Secure Azure-based Java applications Build DevOps CI/CD strategy for Azure-based Java applications Package and deploy Azure-based Java applications on Azure Who This Book Is ForJava developers planning to build Azure-based Java applications and deploy them on Azure. Developers should be aware of the preliminary cloud fundamentals to help them understand the Java capability available on Azure. They do not need to be an expert in Azure to grasp the book’s content and start building Java-based applications using the capability available on Azure. However, they should have a good understanding of the Java programming language and frameworks.

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Jump into the app development world with confidence! iOS Swift 24-Hour Trainer combines book and video lessons in Apple's Swift programming language to prepare you to build iPhone and iPad apps—and distribute them through the Appstore. First, this approachable text covers the fundamentals of Swift by introducing you to iOS development in this language, and presenting best practices for setting up a development environment and using variables, statements, expressions, operators, functions, and closures. Next, you explore common tasks, such as alert views, table views, and collection views. You then deepen your knowledge of Swift by considering network programming and local data storage. Finally, this engaging resource dives into slightly more advanced concepts, such as tab bars, web views, the accelerometer, camera, photo library, Google maps, and core location. Swift was designed by Apple to incorporate modern scripting features while offering simpler, cleaner syntax than Objective-C to maintain a minimal and easy to read style. This more expressive code offers numerous key features, such as closures unified with function pointers, tuples and multiple value returns, generics, and functional programming patterns. Learn how to obtain a device UDID Test your applications on an actual device, so you can see your work in action Distribute your applications outside of the App store, allowing you to test your work with real users Review common reasons why apps are rejected by Apple to strengthen your case when submitting your apps for distribution iOS Swift 24-Hour Trainer is an essential guide to Apple's Swift programming language for beginning programmers.

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Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner! Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple’s ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications. Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book’s clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models—both pre-trained and user-built—with Apple’s CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers: Understand the theoretical concepts and practical applications of machine learning used in predictive data analytics Build, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streaming Develop skills in data acquisition and modeling, classification, and regression. Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS) Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreML Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps.

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Build and deploy applications by leveraging Azure PaaS and serverless services using Azure DevOps and GitHub Actions. This book provides step-by-step explanations of essential concepts, practical examples, and self-assessment questions that will help you gain the necessary expertise to build cloud-native solutions using Microsoft Azure and .NET.The book starts with essential topics that will help get you familiar with the fundamental concepts of Azure, followed by example-based guides on building distributed solutions using Azure Web App, Azure Messaging, and communication services. You will then learn how to implement the knowledge you've thus far gained to build containerized workloads using Azure Container-based services. Next, you will focus on building solutions by using Azure Storage and Data services, where you will go through Azure Blob Storage and learn how to interact with Azure Cosmos DB from applications using the .NET SDK. Moving forward, you will explore how to build intelligent applications using Azure AI and IoT services, including Azure Cognitive Services. In the book's final section, you will explore ways to deploy applications using Azure DevOps and GitHub Actions.After reading this book, you will be able to build scalable, enterprise-grade applications using various Azure services. What You Will Learn Build an ASP.NET 6 Web API to send messages to Azure Service Bus Queue Use and implement Azure Communication Services Build and containerize a .NET API Understand IoT solutions using Azure IoT Hub, Azure Functions, and Azure Cosmos DB Who This Book Is ForExperienced developers and cloud architects working with Microsoft Azure.

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