Blazor in Action
Blazor in Action is a practical guide to building stunning UIs and client-side applications using C# and .NET. You'll use the Blazor frontend framework to create a fun and exciting web application for plotting hiking routes. As you build up your new application, you'll master the key features of Blazor, such as routing, forms and validation, and dynamic and reusable components. By the time you're done, you'll be ready to develop beautiful sites and apps that seamlessly execute your C# code natively in the browser. The book is written to the most recent stable build of Blazor and seamlessly integrates fresh features from .NET 6. Create rich web frontends without relying on JavaScript. Microsoft's Blazor framework uses WebAssembly to extend the ultra-popular ASP.NET platform. In Blazor, you can build interactive web components that run natively in the browser without plug-ins or transpilers. And because it's C# end-to-end, it's easy to share code between the server and your web UI. ...
Blazor in Action is a practical guide to building stunning UIs and client-side applications using C# and .NET. You'll use the Blazor frontend framework to create a fun and exciting web application for plotting hiking routes. As you build up your new application, you'll master the key features of Blazor, such as routing, forms and validation, and dynamic and reusable components. By the time you're done, you'll be ready to develop beautiful sites and apps that seamlessly execute your C# code natively in the browser. The book is written to the most recent stable build of Blazor and seamlessly integrates fresh features from .NET 6. Create rich web frontends without relying on JavaScript. Microsoft's Blazor framework uses WebAssembly to extend the ultra-popular ASP.NET platform. In Blazor, you can build interactive web components that run natively in the browser without plug-ins or transpilers. And because it's C# end-to-end, it's easy to share code between the server and your web UI. ...
Introducing Microsoft SQL Server 2016
Build your database management knowledge with the technical open book, Introducing SQL Server 2016. Get an overview of the SQL Server 2016 features - from in-memory performance and enhanced security to end-to-end mobile business intelligence and advanced analytics. Learn about faster queries, improved security, higher availability, and state-of-the-art database engines; Broaden your data access, get deeper insights from business intelligence analytics, and make your reporting more robust; Expand your data warehouse options with SQL Data Warehouse and Azure SQL Database enhancements. ...
Build your database management knowledge with the technical open book, Introducing SQL Server 2016. Get an overview of the SQL Server 2016 features - from in-memory performance and enhanced security to end-to-end mobile business intelligence and advanced analytics. Learn about faster queries, improved security, higher availability, and state-of-the-art database engines; Broaden your data access, get deeper insights from business intelligence analytics, and make your reporting more robust; Expand your data warehouse options with SQL Data Warehouse and Azure SQL Database enhancements. ...
Automated Machine Learning in Action
Automated Machine Learning in Action reveals how you can automate the burdensome elements of designing and tuning your machine learning systems. It's written in a math-lite and accessible style, and filled with hands-on examples for applying AutoML techniques to every stage of a pipeline. AutoML can even be implemented by machine learning novices! If you're new to ML, you'll appreciate how the book primes you on machine learning basics. Experienced practitioners will love learning how automated tools like AutoKeras and KerasTuner can create pipelines that automatically select the best approach for your task, or tune any customized search space with user-defined hyperparameters, which removes the burden of manual tuning. Machine learning tasks like data pre-processing, feature selection, and model optimization can be time-consuming and highly technical. Automated machine learning, or AutoML, applies pre-built solutions to these chores, eliminating errors caused by manual processing. ...
Automated Machine Learning in Action reveals how you can automate the burdensome elements of designing and tuning your machine learning systems. It's written in a math-lite and accessible style, and filled with hands-on examples for applying AutoML techniques to every stage of a pipeline. AutoML can even be implemented by machine learning novices! If you're new to ML, you'll appreciate how the book primes you on machine learning basics. Experienced practitioners will love learning how automated tools like AutoKeras and KerasTuner can create pipelines that automatically select the best approach for your task, or tune any customized search space with user-defined hyperparameters, which removes the burden of manual tuning. Machine learning tasks like data pre-processing, feature selection, and model optimization can be time-consuming and highly technical. Automated machine learning, or AutoML, applies pre-built solutions to these chores, eliminating errors caused by manual processing. ...
Payara Micro Revealed
Develop, configure, and deploy Java cloud-native applications using Payara Micro. This book demystifies Java cloud-native application development using standard Microprofile APIs and covers Payara-specific features such as automatic clustering and application initialization performance improvements. You will learn how to improve startup performance by taking advantage of class data sharing, and configure cloud-native applications via standard development tools such as Maven and Gradle. The book also clarifies how to develop functionality necessary in a cloud environment, such as health checks and request tracing, using MicroProfile APIs. The book begins by showing how to develop microservices using RESTful web services, followed by how to create microservice clients using MicroProfile and the REST client API. Dependency Injection via Jakarta Context and Dependency Injection (CDI) is also covered. Various approaches to application configuration are covered as well, including property ...
Develop, configure, and deploy Java cloud-native applications using Payara Micro. This book demystifies Java cloud-native application development using standard Microprofile APIs and covers Payara-specific features such as automatic clustering and application initialization performance improvements. You will learn how to improve startup performance by taking advantage of class data sharing, and configure cloud-native applications via standard development tools such as Maven and Gradle. The book also clarifies how to develop functionality necessary in a cloud environment, such as health checks and request tracing, using MicroProfile APIs. The book begins by showing how to develop microservices using RESTful web services, followed by how to create microservice clients using MicroProfile and the REST client API. Dependency Injection via Jakarta Context and Dependency Injection (CDI) is also covered. Various approaches to application configuration are covered as well, including property ...
Introduction to Scientific Programming with Python
This open book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies. ...
This open book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies. ...
Azure Machine Learning
This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. ...
This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. ...
Learn Java 17 Programming, 2nd Edition
Java is one of the most preferred languages among developers. It is used in everything right from smartphones and game consoles to even supercomputers, and its new features simply add to the richness of the language. This book on Java programming begins by helping you learn how to install the Java Development Kit. You'll then focus on understanding object-oriented programming (OOP), with exclusive insights into concepts such as abstraction, encapsulation, inheritance, and polymorphism, which will help you when programming for real-world apps. Next, you'll cover fundamental programming structures of Java such as data structures and algorithms that will serve as the building blocks for your apps with the help of sample programs and practice examples. You'll also delve into core programming topics that will assist you with error handling, debugging, and testing your apps. As you progress, you'll move on to advanced topics such as Java libraries, database management, and network program ...
Java is one of the most preferred languages among developers. It is used in everything right from smartphones and game consoles to even supercomputers, and its new features simply add to the richness of the language. This book on Java programming begins by helping you learn how to install the Java Development Kit. You'll then focus on understanding object-oriented programming (OOP), with exclusive insights into concepts such as abstraction, encapsulation, inheritance, and polymorphism, which will help you when programming for real-world apps. Next, you'll cover fundamental programming structures of Java such as data structures and algorithms that will serve as the building blocks for your apps with the help of sample programs and practice examples. You'll also delve into core programming topics that will assist you with error handling, debugging, and testing your apps. As you progress, you'll move on to advanced topics such as Java libraries, database management, and network program ...
Modern Java EE Design Patterns
With the ascent of DevOps, microservices, containers, and cloud-based development platforms, the gap between state-of-the-art solutions and the technology that enterprises typically support has greatly increased. But as Markus Eisele explains in this O'Reilly report, some enterprises are now looking to bridge that gap by building microservice-based architectures on top of Java EE. Can it be done? Is it even a good idea? Eisele thoroughly explores the possibility and provides savvy advice for enterprises that want to move ahead. The issue is complex: Java EE wasn't built with the distributed application approach in mind, but rather as one monolithic server runtime or cluster hosting many different applications. If you're part of an enterprise development team investigating the use of microservices with Java EE, this book will help you: - Understand the challenges of starting a greenfield development vs tearing apart an existing brownfield application into services; - Examine your b ...
With the ascent of DevOps, microservices, containers, and cloud-based development platforms, the gap between state-of-the-art solutions and the technology that enterprises typically support has greatly increased. But as Markus Eisele explains in this O'Reilly report, some enterprises are now looking to bridge that gap by building microservice-based architectures on top of Java EE. Can it be done? Is it even a good idea? Eisele thoroughly explores the possibility and provides savvy advice for enterprises that want to move ahead. The issue is complex: Java EE wasn't built with the distributed application approach in mind, but rather as one monolithic server runtime or cluster hosting many different applications. If you're part of an enterprise development team investigating the use of microservices with Java EE, this book will help you: - Understand the challenges of starting a greenfield development vs tearing apart an existing brownfield application into services; - Examine your b ...
TensorFlow in Action
In TensorFlow in Action, you'll dig into the newest version of Google's amazing TensorFlow framework as you learn to create incredible deep learning applications. Author Thushan Ganegedara uses quirky stories, practical examples, and behind-the-scenes explanations to demystify concepts otherwise trapped in dense academic papers. As you dive into modern deep learning techniques like transformer and attention models, you'll benefit from the unique insights of a top StackOverflow contributor for deep learning and NLP. Google's TensorFlow framework sits at the heart of modern deep learning. Boasting practical features like multi-GPU support, network data visualization, and easy production pipelines using TensorFlow Extended (TFX), TensorFlow provides the most efficient path to professional AI applications. And the Keras library, fully integrated into TensorFlow 2, makes it a snap to build and train even complex models for vision, language, and more. TensorFlow in Action teaches you t ...
In TensorFlow in Action, you'll dig into the newest version of Google's amazing TensorFlow framework as you learn to create incredible deep learning applications. Author Thushan Ganegedara uses quirky stories, practical examples, and behind-the-scenes explanations to demystify concepts otherwise trapped in dense academic papers. As you dive into modern deep learning techniques like transformer and attention models, you'll benefit from the unique insights of a top StackOverflow contributor for deep learning and NLP. Google's TensorFlow framework sits at the heart of modern deep learning. Boasting practical features like multi-GPU support, network data visualization, and easy production pipelines using TensorFlow Extended (TFX), TensorFlow provides the most efficient path to professional AI applications. And the Keras library, fully integrated into TensorFlow 2, makes it a snap to build and train even complex models for vision, language, and more. TensorFlow in Action teaches you t ...
Genomics in the Azure Cloud
This practical guide bridges the gap between general cloud computing architecture in Microsoft Azure and scientific computing for bioinformatics and genomics. You'll get a solid understanding of the architecture patterns and services that are offered in Azure and how they might be used in your bioinformatics practice. You'll get code examples that you can reuse for your specific needs. And you'll get plenty of concrete examples to illustrate how a given service is used in a bioinformatics context. You'll also get valuable advice on how to: Use enterprise platform services to easily scale your bioinformatics workloads; Organize, query, and analyze genomic data at scale; Build a genomics data lake and accompanying data warehouse; Use Azure Machine Learning to scale your model training, track model performance, and deploy winning models; Orchestrate and automate processing pipelines using Azure Data Factory and Databricks; Cloudify your organization's existing bioinformatics pipelines ...
This practical guide bridges the gap between general cloud computing architecture in Microsoft Azure and scientific computing for bioinformatics and genomics. You'll get a solid understanding of the architecture patterns and services that are offered in Azure and how they might be used in your bioinformatics practice. You'll get code examples that you can reuse for your specific needs. And you'll get plenty of concrete examples to illustrate how a given service is used in a bioinformatics context. You'll also get valuable advice on how to: Use enterprise platform services to easily scale your bioinformatics workloads; Organize, query, and analyze genomic data at scale; Build a genomics data lake and accompanying data warehouse; Use Azure Machine Learning to scale your model training, track model performance, and deploy winning models; Orchestrate and automate processing pipelines using Azure Data Factory and Databricks; Cloudify your organization's existing bioinformatics pipelines ...