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Alex Forrester, Eran Boudjnah, Alexandru Dumbravan, Jomar Tigcal
Are you keen to get started building Android 11 apps, but don’t know where to start? How to Build Android Apps with Kotlin is a comprehensive guide that will help kick-start your Android development practice.This book starts with the fundamentals of app development, enabling you to utilize Android Studio and Kotlin to get started building Android projects. You'll learn how to create apps and run them on virtual devices through guided exercises. Progressing through the chapters, you'll delve into Android’s RecyclerView to make the most of lists, images, and maps, and see how to fetch data from a web service.Moving ahead, you'll get to grips with testing, learn how to keep your architecture clean, understand how to persist data, and gain basic knowledge of the dependency injection pattern. Finally, you'll see how to publish your apps on the Google Play store.You'll work on realistic projects that are split up into bitesize exercises and activities, allowing you to challenge yourself in an enjoyable and attainable way. You'll build apps to create quizzes, read news articles, check weather reports, store recipes, retrieve movie information, and remind you where you parked your car.By the end of this book, you'll have the skills and confidence to build your own creative Android applications using Kotlin.
Lars Gyrup Brink Nielsen, Jacob Andresen, Santosh Yadav
Angular Ivy is the latest rendering engine and compiler introduced in Angular. Ivy helps frontend developers to make their Angular applications faster, better optimized, and more robust. This easy-to-follow guide will help you get to grips with the new features of Angular Ivy and show you how to migrate your Angular apps from View Engine to Ivy.You'll begin by learning about the most popular features of Angular Ivy with the help of simple stand-alone examples and realize its capabilities by working on a real-world application project. You'll then discover strategies to improve your developer workflow through new debugging APIs, testing APIs, and configurations that support higher code quality and productive development features. Throughout the book, you'll explore essential components of Angular, such as Angular Component Dev Kit (CDK), Ahead-of-time (AOT) compilation, and Angular command line interface (CLI). Finally, you'll gain a clear understanding of these components along with Angular Ivy which will help you update your Angular applications with modern features.By the end of this Angular Ivy book, you will learn about the core features of Angular Ivy, discover how to migrate your Angular View Engine application, and find out how to set up a high-quality Angular Ivy project.
PHP 7 Programming Blueprints. Rethink PHP
When it comes to modern web development, performance is everything. The latest version of PHP has been improvised and updated to make it easier to build for performance, improved engine execution, better memory usage, and a new and extended set of tools. If you’re a web developer, what’s not to love? This guide will show you how to make full use of PHP 7 with a range of practical projects that will not only teach you the principles, but also show you how to put them into practice. It will push and extend your skills, helping you to become a more confident and fluent PHP developer.You’ll find out how to build a social newsletter service, a simple blog with a search capability using Elasticsearch, as well as a chat application. We’ll also show you how to create a RESTful web service, a database class to manage a shopping cart on an e-commerce site and how to build an asynchronous microservice architecture. With further guidance on using reactive extensions in PHP, we’re sure that you’ll find everything you need to take full advantage of PHP 7. So dive in now!
Graphs have become increasingly integral to powering the products and services we use in our daily lives, driving social media, online shopping recommendations, and even fraud detection. With this book, you’ll see how a good graph data model can help enhance efficiency and unlock hidden insights through complex network analysis.Graph Data Modeling in Python will guide you through designing, implementing, and harnessing a variety of graph data models using the popular open source Python libraries NetworkX and igraph. Following practical use cases and examples, you’ll find out how to design optimal graph models capable of supporting a wide range of queries and features. Moreover, you’ll seamlessly transition from traditional relational databases and tabular data to the dynamic world of graph data structures that allow powerful, path-based analyses. As well as learning how to manage a persistent graph database using Neo4j, you’ll also get to grips with adapting your network model to evolving data requirements.By the end of this book, you’ll be able to transform tabular data into powerful graph data models. In essence, you’ll build your knowledge from beginner to advanced-level practitioner in no time.
Red Hat Enterprise Linux Server Cookbook. Click here to enter text
Dominating the server market, the Red Hat Enterprise Linux operating system gives you the support you need to modernize your infrastructure and boost your organization’s efficiency. Combining both stability and flexibility, RHEL helps you meet the challenges of today and adapt to the demands of tomorrow.This practical Cookbook guide will help you get to grips with RHEL 7 Server and automating its installation. Designed to provide targeted assistance through hands-on recipe guidance, it will introduce you to everything you need to know about KVM guests and deploying multiple standardized RHEL systems effortlessly. Get practical reference advice that will make complex networks setups look like child’s play, and dive into in-depth coverage of configuring a RHEL system. Also including full recipe coverage of how to set up, configuring, and troubleshoot SELinux, you’ll also discover how secure your operating system, as well as how to monitor it.
Mark Hodnett, Joshua F. Wiley, Yuxi (Hayden) Liu, Pablo Maldonado
Deep learning has a range of practical applications in several domains, while R is the preferred language for designing and deploying deep learning models.This Learning Path introduces you to the basics of deep learning and even teaches you to build a neural network model from scratch. As you make your way through the chapters, you’ll explore deep learning libraries and understand how to create deep learning models for a variety of challenges, right from anomaly detection to recommendation systems. The Learning Path will then help you cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale deep learning in the cloud, in addition to model optimization, overfitting, and data augmentation. Through real-world projects, you’ll also get up to speed with training convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory networks (LSTMs) in R.By the end of this Learning Path, you’ll be well-versed with deep learning and have the skills you need to implement a number of deep learning concepts in your research work or projects.