Hands On High Performance With Spring 5

A hands-on guide to creating, monitoring, and tuning a high performance Spring web application Key Features Understand common performance pitfalls and improve your application's performance Build and deploy strategies for complex applications using the microservice architecture Understand internals of JVM - the core of all Java Runtime Environments Book Description While writing an application, performance is paramount. Performance tuning for real-world applications often involves activities geared toward detecting bottlenecks. The recent release of Spring 5.0 brings major advancements in the rich API provided by the Spring framework, which means developers need to master its tools and techniques to achieve high performance applications. Hands-On High Performance with Spring 5 begins with the Spring framework's core features, exploring the integration of different Spring projects. It proceeds to evaluate various Spring specifications to identify those adversely affecting performance. You will learn about bean wiring configurations, aspect-oriented programming, database interaction, and Hibernate to focus on the metrics that help identify performance bottlenecks. You will also look at application monitoring, performance optimization, JVM internals, and garbage collection optimization. Lastly, the book will show you how to leverage the microservice architecture to build a high performance and resilient application. By the end of the book, you will have gained an insight into various techniques and solutions to build and troubleshoot high performance Spring-based applications. What you will learn Master programming best practices and performance improvement with bean wiring Analyze the performance of various AOP implementations Explore database interactions with Spring to optimize design and configuration Solve Hibernate performance issues and traps Leverage multithreading and concurrent programming to improve application performance Gain a solid foundation in JVM performance tuning using various tools Learn the key concepts of the microservice architecture and how to monitor them Perform Spring Boot performance tuning, monitoring, and health checks Who this book is for If you’re a Spring developer who’d like to build high performance applications and have more control over your application's performance in production and development, this book is for you. Some familiarity with Java, Maven, and Eclipse is necessary.

Develop cloud native applications with microservices using Spring Boot, Spring Cloud, and Spring Cloud Data Flow About This Book Explore the new features and components in Spring Evolve towards micro services and cloud native applications Gain powerful insights into advanced concepts of Spring and Spring Boot to develop applications more effectively Understand the basics of Kotlin and use it to develop a quick service with Spring Boot Who This Book Is For This book is for an experienced Java developer who knows the basics of Spring, and wants to learn how to use Spring Boot to build applications and deploy them to the cloud. What You Will Learn Explore the new features in Spring Framework 5.0 Build microservices with Spring Boot Get to know the advanced features of Spring Boot in order to effectively develop and monitor applications Use Spring Cloud to deploy and manage applications on the Cloud Understand Spring Data and Spring Cloud Data Flow Understand the basics of reactive programming Get to know the best practices when developing applications with the Spring Framework Create a new project using Kotlin and implement a couple of basic services with unit and integration testing In Detail Spring 5.0 is due to arrive with a myriad of new and exciting features that will change the way we've used the framework so far. This book will show you this evolution—from solving the problems of testable applications to building distributed applications on the cloud. The book begins with an insight into the new features in Spring 5.0 and shows you how to build an application using Spring MVC. You will realize how application architectures have evolved from monoliths to those built around microservices. You will then get a thorough understanding of how to build and extend microservices using Spring Boot. You will also understand how to build and deploy Cloud-Native microservices with Spring Cloud. The advanced features of Spring Boot will be illustrated through powerful examples. We will be introduced to a JVM language that's quickly gaining popularity - Kotlin. Also, we will discuss how to set up a Kotlin project in Eclipse. By the end of the book, you will be equipped with the knowledge and best practices required to develop microservices with the Spring Framework. Style and approach This book follows an end-to-end tutorial approach with lots of examples and sample applications, covering the major building blocks of the Spring framework.

Discover how different software architectural models can help you solve problems, and learn best practices for the software development cycle Key Features Learn concepts related to software architecture and embrace them using the latest features of Spring 5 Discover architectural models and learn when to apply them Gain knowledge of architectural principles and how they can be used to provide accountability and rationale for architectural decisions Book Description Spring 5 and its ecosystem can be used to build robust architectures effectively. Software architecture is the underlying piece that helps us accomplish our business goals whilst supporting the features that a product demands. This book explains in detail how to choose the right architecture and apply best practices during your software development cycle to avoid technical debt and support every business requirement. Choosing the right architecture model to support your business requirements is one of the key decisions you need to take when a new product is being created from scratch or is being refactored to support new business demands. This book gives you insights into the most common architectural models and guides you when and where they can be used. During this journey, you’ll see cutting-edge technologies surrounding the Spring products, and understand how to use agile techniques such as DevOps and continuous delivery to take your software to production effectively. By the end of this book, you’ll not only know the ins and outs of Spring, but also be able to make critical design decisions that surpass your clients’ expectations. What you will learn Understand the key principles of software architecture Uncover the most common architectural models available Analyze scenarios where an architecture model should be used Implement agile techniques to take your software to production Secure the products you are working on Master tricks that will help you build high-performant applications Use cutting-edge technologies to build products Who this book is for If you’re an experienced Spring developer aspiring to become an architect of enterprise-grade applications, this book is for you. It’s also ideal for software architects who want to leverage Spring to create effective application blueprints.

Spring Boot and React allow us to build powerful full-stack applications and also demonstrate a modern full-stack app in practice. React is a modern JavaScript library for building fast and reliable user interfaces. You will also master the process of full-stack development by leveraging Spring Boot and React

Today, businesses need a new type of system that can remain responsive at all times. This result is achievable and is called reactive, which means it reacts to changes. The development of such systems is a complex task, requiring a deep understanding of the domain. The developers of the Spring Framework help with the reactive version

Learn how to deploy effective deep learning solutions on cross-platform applications built using TensorFlow Lite, ML Kit, and Flutter Key FeaturesWork through projects covering mobile vision, style transfer, speech processing, and multimedia processingCover interesting deep learning solutions for mobileBuild your confidence in training models, performance tuning, memory optimization, and neural network deployment through every projectBook Description Deep learning is rapidly becoming the most popular topic in the mobile app industry. This book introduces trending deep learning concepts and their use cases with an industrial and application-focused approach. You will cover a range of projects covering tasks such as mobile vision, facial recognition, smart artificial intelligence assistant, augmented reality, and more. With the help of eight projects, you will learn how to integrate deep learning processes into mobile platforms, iOS, and Android. This will help you to transform deep learning features into robust mobile apps efficiently. You’ll get hands-on experience of selecting the right deep learning architectures and optimizing mobile deep learning models while following an application oriented-approach to deep learning on native mobile apps. We will later cover various pre-trained and custom-built deep learning model-based APIs such as machine learning (ML) Kit through Firebase. Further on, the book will take you through examples of creating custom deep learning models with TensorFlow Lite. Each project will demonstrate how to integrate deep learning libraries into your mobile apps, right from preparing the model through to deployment. By the end of this book, you’ll have mastered the skills to build and deploy deep learning mobile applications on both iOS and Android. What you will learnCreate your own customized chatbot by extending the functionality of Google AssistantImprove learning accuracy with the help of features available on mobile devicesPerform visual recognition tasks using image processingUse augmented reality to generate captions for a camera feedAuthenticate users and create a mechanism to identify rare and suspicious user interactionsDevelop a chess engine based on deep reinforcement learningExplore the concepts and methods involved in rolling out production-ready deep learning iOS and Android applicationsWho this book is for This book is for data scientists, deep learning and computer vision engineers, and natural language processing (NLP) engineers who want to build smart mobile apps using deep learning methods. You will also find this book useful if you want to improve your mobile app’s user interface (UI) by harnessing the potential of deep learning. Basic knowledge of neural networks and coding experience in Python will be beneficial to get started with this book.

一本书轻松读懂金融科技的核心内涵 Key Features 一本书轻松读懂金融科技的核心内涵; 众多业界人士推荐,内容通俗易懂; 立足AI视角,解读金融业务新形态; 书中囊括丰富的算法讲解和代码示例; 更有一系列高效的金融科技解决方案。 Book Description近年来,人工智能在各个领域被广泛应用,但对于很多金融从业人员来说,人工智能仍然给人一种高深莫测的感觉。本书旨在从新技术(如人工智能)的视角给出金融业务的新兴解决方案。 本书内容通俗易懂,不仅揭示了人工智能在金融业中的重要性,还结合机器学习算法和示例给出了一系列的金融科技解决方案,涉及时间序列分析、强化学习、预测分析、自动化投资组合管理、情绪分析、自然语言处理等知识点。此外,本书还结合现实工作总结了相关的注意事项。 本书适合传统金融行业的从业者以及新兴金融科技领域的实践者阅读。读者可从本书深入浅出的知识点和案例中了解到人工智能的魅力,为更好地运用人工智能技术赋能金融业务做好准备。What you will learn 轻松读懂金融科技的核心内涵; 人工智能在金融业中的重要性 一系列的金融科技解决方案 Who this book is for 本书适合传统金融行业的从业者以及新兴金融科技领域的实践者阅读。读者可从本书深入浅出的知识点和案例中了解到人工智能的魅力,为更好地运用人工智能技术赋能金融业务做好准备。

Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications Key FeaturesBuild independent machine learning (ML) systems leveraging the best features of R 3.5Understand and apply different machine learning techniques using real-world examplesUse methods such as multi-class classification, regression, and clusteringBook Description Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML ,using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You’ll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you’ll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You’ll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you’ll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you’ll be equipped with the skills to deploy ML techniques in your own projects or at work. What you will learnPrepare data for machine learning methods with easeUnderstand how to write production-ready code and package it for useProduce simple and effective data visualizations for improved insightsMaster advanced methods, such as Boosted Trees and deep neural networksUse natural language processing to extract insights in relation to textImplement tree-based classifiers, including Random Forest and Boosted TreeWho this book is for This book is for data science professionals, machine learning engineers, or anyone who is looking for the ideal guide to help them implement advanced machine learning algorithms. The book will help you take your skills to the next level and advance further in this field. Working knowledge of machine learning with R is mandatory.