Take Web development skills from the browser to the Web server with Node, the programming framework that enables users to write data-driven applications with a language they already know: JavaScript.

Learning Node.js A Hands-On Guide to Building Web Applications in JavaScript Node.js makes it far easier to create fast, compact, and reliable web/network applications and web servers, and is rapidly becoming indispensable to modern web developers. Learning Node.js brings together the knowledge and JavaScript code you need to build master the Node.js platform and build server-side applications with extraordinary speed and scalability. You’ll start by installing and running Node.js, understanding the extensions it uses, and quickly writing your first app. Next, building on the basics, you’ll write more capable application servers and extend them with today’s most powerful Node.js tools and modules. Finally, you’ll discover today’s best practices for testing, running Node.js code on production servers, and writing command-line utilities. Throughout the book, author Marc Wandschneider teaches by walking you line-by-line through carefully crafted examples, demonstrating proven techniques for creating highly efficient applications and servers. Build Node.js solutions that leverage your current JavaScript skills Master Node.js nonblocking IO and async programming Handle more requests and increase your application’s flexibility Use and write your own modules Perform common JSON/web server tasks Use browsers to generate pages on the fly via Ajax calls and template libraries Simplify development with the express framework Create database back-ends using popular NoSQL and relational databases Deploy and run Node.js apps on Unix/OS X or Windows servers Take advantage of multiprocessor hardware Support virtual hosts and SSL/HTTPS security Test Node.js programs that mix synchronous, async, and RESTful server API functionality

A comprehensive, easy-to-follow guide to creating complete Node apps and understanding how to build, deploy, and test your own apps. Key Features Entirely project-based and practical Explains the "Why" of Node.js features, not just the "how", providing you with a deep understanding and enabling you to easily apply concepts in your own applications Covers the full range of technologies around Node.js – NPM, version control with Git, and much more Book Description Learning Node.js Development is a practical, project-based book that provides you with all you need to get started as a Node.js developer. Node is a ubiquitous technology on the modern web, and an essential part of any web developers' toolkit. If you are looking to create real-world Node applications, or you want to switch careers or launch a side project to generate some extra income, then you're in the right place. This book has been written around a single goal—turning you into a professional Node developer capable of developing, testing, and deploying real-world production applications. Learning Node.js Development is built from the ground up around the latest version of Node.js (version 9.x.x). You'll be learning all the cutting-edge features available only in the latest software versions. This book cuts through the mass of information available around Node and delivers the essential skills that you need to become a Node developer. It takes you through creating complete apps and understanding how to build, deploy, and test your own Node apps. It maps out everything in a comprehensive, easy-to-follow package designed to get you up and running quickly. What you will learn Learn the fundamentals of Node Build apps that respond to user input Master working with servers Learn how to test and debug applications Deploy and update your apps in the real world Create responsive asynchronous web applications Who this book is for This book targets anyone looking to launch their own Node applications, switch careers, or freelance as a Node developer. You should have a basic understanding of JavaScript in order to follow this course.

Solve practical real-world problems using JavaScript and Node.js About This Book Learn the concepts of Node.js to gain a high-level understanding of the Node.js execution model Build an interactive web application with MongoDB and Redis and create your own JavaScript modules that work both on the client side and server side Familiarize yourself with the new features of Node.js and JavaScript with this exclusive step-by-step guide Who This Book Is For This book is for developers who want to learn JavaScript and Node.js. Previous experience with programming is desired, but no JavaScript or Node.js knowledge is required. The book focuses mostly on web development, such as networking, serving dynamic pages, and real-time client-server communication. What You Will Learn Understand which problems Node.js best solves Write idiomatic JavaScript and Node.js code Build web applications and command-line tools Minimise complexity and efficiently solve difficult problems Test and deploy Node.js applications Work with persistent data Implement real-time client-server applications Integrate .NET and Node.js code In Detail Node.js is an open source, cross-platform runtime environment that allows you to use JavaScript to develop server-side web applications. This short guide will help you develop applications using JavaScript and Node.js, leverage your existing programming skills from .NET or Java, and make the most of these other platforms through understanding the Node.js programming model. You will learn how to build web applications and APIs in Node, discover packages in the Node.js ecosystem, test and deploy your Node.js code, and more. Finally, you will discover how to integrate Node.js and .NET code. Style and approach This is a step-by-step and practical guide to Node.js for .Net developers. It covers the fundamentals relating to typical applications. The focus is on providing the practical skills required to develop applications, with a summary of the key concepts covered.

Make use of Node.js to learn the development of a simple yet scalable cross-platform mobile application About This Book Use Node.js to satisfy the core backend requirements of modern apps, including user management, security, data access, and real-time data communication Build practical real-world mobile applications, which will give you the necessary knowledge to build your very own mobile solutions Step-by-step development of projects using Ionic Framework as the frontend and Node.js for the backend supported by a MongoDB database Who This Book Is For This book is intended for web developers of all levels of expertise who want to deep dive into cross-platform mobile application development without going through the pains of understanding the languages and native frameworks that form an integral part of developing for different mobile platforms. This book is also for you if you are a developer who wants to capitalize on the MobileFirst strategy and so are going to use JavaScript for your complete stack. What You Will Learn Develop an API from scratch Set up a MongoDB Database as part of your mobile application backend Deploy a cross-platform mobile application from the command line Incorporate features within your mobile application that use native phone features such as a gyroscope, GPS, and accelerometer Implement mobile applications that use web-enabled APIs Build a mobile application with real-time chat messaging features Develop a secure mobile application that is capable of functioning with real-time data In Detail Node.js is a massively popular JavaScript library that lets you use JavaScript to easily program scalable network applications and web services. People approaching Node.js for the first time are often attracted by its efficiency, scalability, and the fact that it's based on JavaScript, the language of the Web, which means that developers can use the same language to write backend code. Also, it's increasingly being seen as a "modern" replacement for PHP in web development, which relies on fast-paced data exchange. The growing community and the large amount of available modules makes Node.js one of the most attractive development environments. This book takes a step-wise and incremental approach toward developing cross-platform mobile technologies using existing web technologies. This will allow you to truly understand and become proficient in developing cross-platform mobile applications with Node.js, Ionic Framework, and MongoDB. The book starts off by introducing all the necessary requirements and knowledge to build a mobile application with a companion web service. It covers the ability to create an API from scratch and implement a comprehensive user database that will give you the opportunity to offer a mobile application with a personalized experience. Midway through the book, you will learn the basic processes to create a successful mobile application. You will also gain higher-level knowledge, allowing you to develop a functional and secure mobile application to ensure a seamless user experience for end users. Finally, the book ends with more advanced projects, which will bring together all the knowledge and expertise developed in the previous chapters to create a practical and functional mobile-application that has useful real-world features. Style and approach This book is an easy-to-follow guide that takes a step-wise approach in giving expertise and knowledge to help you truly understand what is needed to create a memorable user experience for end users. Each topic is placed in the context of the bigger picture, that is, to create cross-platform mobile applications using existing technologies.

The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications. Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics. Applied Data Science Track: Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation. Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.

This book offers the latest advances and results in the fields of Machine Learning and Deep Learning for Wireless Communication and provides positive and critical discussions on the challenges and prospects. It provides a broad spectrum in understanding the improvements in Machine Learning and Deep Learning that are motivating by the specific constraints posed by wireless networking systems. The book offers an extensive overview on intelligent Wireless Communication systems and its underlying technologies, research challenges, solutions, and case studies. It provides information on intelligent wireless communication systems and its models, algorithms and applications. The book is written as a reference that offers the latest technologies and research results to various industry problems.

This book constitutes the refereed proceedings of the 20th International Conference on Algorithmic Learning Theory, ALT 2009, held in Porto, Portugal, in October 2009, co-located with the 12th International Conference on Discovery Science, DS 2009. The 26 revised full papers presented together with the abstracts of 5 invited talks were carefully reviewed and selected from 60 submissions. The papers are divided into topical sections of papers on online learning, learning graphs, active learning and query learning, statistical learning, inductive inference, and semisupervised and unsupervised learning. The volume also contains abstracts of the invited talks: Sanjoy Dasgupta, The Two Faces of Active Learning; Hector Geffner, Inference and Learning in Planning; Jiawei Han, Mining Heterogeneous; Information Networks By Exploring the Power of Links, Yishay Mansour, Learning and Domain Adaptation; Fernando C.N. Pereira, Learning on the Web.

Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects. If you’ve been curious about machine learning but didn’t know where to start, this is the book you’ve been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning teaches you the why of deep learning and will inspire you to explore further. All you need is basic familiarity with computer programming and high school math—the book will cover the rest. After an introduction to Python, you’ll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models’ performance. You’ll also learn: How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector Machines How neural networks work and how they’re trained How to use convolutional neural networks How to develop a successful deep learning model from scratch You’ll conduct experiments along the way, building to a final case study that incorporates everything you’ve learned. The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning will give you the skills and confidence to dive into your own machine learning projects.

This book presents an up-to-date tutorial and overview on learning technologies such as random forests, sparsity, and low-rank matrix estimation and cutting-edge visual/signal processing techniques, including face recognition, Kalman filtering, and multirate DSP. It discusses the applications that make use of deep learning, convolutional neural networks, random forests, etc.