Continuous Integration, Delivery, and Deployment. Reliable and faster software releases with automating builds, tests, and deployment

Sander Rossel

The challenge faced by many teams while implementing Continuous Deployment is that it requires the use of many tools and processes that all work together. Learning and implementing all these tools (correctly) takes a lot of time and effort, leading people to wonder whether it's really worth it. This book sets up a project to show you the different steps, processes, and tools in Continuous Deployment and the actual problems they solve.We start by introducing Continuous Integration (CI), deployment, and delivery as well as providing an overview of the tools used in CI. You'll then create a web app and see how Git can be used in a CI environment. Moving on, you'll explore unit testing using Jasmine and browser testing using Karma and Selenium for your app. You'll also find out how to automate tasks using Gulp and Jenkins. Next, you'll get acquainted with database integration for different platforms, such as MongoDB and PostgreSQL. Finally, you'll set up different Jenkins jobs to integrate with Node.js and C# projects, and Jenkins pipelines to make branching easier.By the end of the book, you'll have implemented Continuous Delivery and deployment from scratch.

Mastering Swift 3 - Linux. Click here to enter text

Jon Hoffman

Swift is a modern, fast, and safe programming language created by Apple. Writing Swift is interactive and fun, the syntax is concise yet expressive, and the code runs lightning-fast. Swift’s move to open source has been embraced with open arms and has seen increased adoption in the Linux platform.Our book will introduce you to the Swift language, further delving into all the key concepts you need to create applications for desktop, server, and embedded Linux platforms. We will teach you the best practices to design an application with Swift 3 via design patterns and Protocol-Oriented Programming. Further on, you will learn how to catch and respond to errors within your application. When you have gained a strong knowledge of using Swift in Linux, we’ll show you how to build IoT and robotic projects using Swift on single board computers. By the end of the book, you will have a solid understanding of the Swift Language with Linux and will be able to create your own applications with ease.

CompTIA Linux+ Certification Guide. A comprehensive guide to achieving LX0-103 and LX0-104 certifications with mock exams

Philip Inshanally

The Linux+ certification provides a broad awareness of Linux operating systems, while giving professionals an upper hand in the IT industry. With this certification, you’ll be equipped with the all-important knowledge of installation, operation, administration, and troubleshooting services.This CompTIA Linux+ Certification Guide will give you an overview of the system architecture. You’ll understand how to install and uninstall Linux distributions, followed by working with various package managers. You’ll then move on to manipulating files and processes at the command-line interface (CLI) and creating, monitoring, killing, restarting, and modifying processes.As you progress, you’ll be equipped to work with display managers and learn how you can create, modify, and remove user accounts and groups, as well as understand how to automate tasks. The last set of chapters will help you configure dates and set up local and remote system logging. In addition to this, you’ll explore different internet protocols, and delve into network configuration, security administration, Shell scripting, and SQL management.By the end of this book, you’ll not only have got to grips with all the modules you need to study for the LX0-103 and LX0-104 certification exams, but you’ll also be able to test your understanding with practice questions and mock exams.

Python Deep Learning Cookbook. Over 75 practical recipes on neural network modeling, reinforcement learning, and transfer learning using Python

Indra den Bakker

Deep Learning is revolutionizing a wide range of industries. For many applications, deep learning has proven to outperform humans by making faster and more accurate predictions. This book provides a top-down and bottom-up approach to demonstrate deep learning solutions to real-world problems in different areas. These applications include Computer Vision, Natural Language Processing, Time Series, and Robotics. The Python Deep Learning Cookbook presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, a discussion on corresponding pros and cons of implementing the proposed solution using one of the popular frameworks like TensorFlow, PyTorch, Keras and CNTK is provided. The book includes recipes that are related to the basic concepts of neural networks. All techniques s, as well as classical networks topologies. The main purpose of this book is to provide Python programmers a detailed list of recipes to apply deep learning to common and not-so-common scenarios.

Julia 1.0 Programming Cookbook. Over 100 numerical and distributed computing recipes for your daily data science work?ow

Bogumił Kamiński, Przemysław Szufel

Julia, with its dynamic nature and high-performance, provides comparatively minimal time for the development of computational models with easy-to-maintain computational code. This book will be your solution-based guide as it will take you through different programming aspects with Julia.Starting with the new features of Julia 1.0, each recipe addresses a specific problem, providing a solution and explaining how it works. You will work with the powerful Julia tools and data structures along with the most popular Julia packages. You will learn to create vectors, handle variables, and work with functions. You will be introduced to various recipes for numerical computing, distributed computing, and achieving high performance. You will see how to optimize data science programs with parallel computing and memory allocation. We will look into more advanced concepts such as metaprogramming and functional programming. Finally, you will learn how to tackle issues while working with databases and data processing, and will learn about on data science problems, data modeling, data analysis, data manipulation, parallel processing, and cloud computing with Julia.By the end of the book, you will have acquired the skills to work more effectively with your data

Learn C# in 7 days. Get up and running with C# 7 with async main, tuples, pattern matching, LINQ, regex, indexers, and more

Gaurav Aroraa

This book takes a unique approach to teach C# to absolute beginners. You’ll learn the basics of the language in seven days. It takes a practical approach to explain the important concepts that build the foundation of the C# programming language. The book begins by teaching you the basic fundamentals using real-world practical examples and gets you acquainted with C# programming. We cover some important features and nuances of the language in a hands-on way, helping you grasp the concepts in a fluid manner. Later, you’ll explore the concepts of Object-Oriented Programming (OOP) through a real-world example. Then we dive into advanced-level concepts such as generics and collections, and you’ll get acquainted with objects and LINQ. Towards the end, you’ll build an application that covers all the concepts explained in the book. By the end of this book, you will have next-level skills and a good knowledge of the fundamentals of C#.

Hands-On Meta Learning with Python. Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow

Sudharsan Ravichandiran

Meta learning is an exciting research trend in machine learning, which enables a model to understand the learning process. Unlike other ML paradigms, with meta learning you can learn from small datasets faster.Hands-On Meta Learning with Python starts by explaining the fundamentals of meta learning and helps you understand the concept of learning to learn. You will delve into various one-shot learning algorithms, like siamese, prototypical, relation and memory-augmented networks by implementing them in TensorFlow and Keras. As you make your way through the book, you will dive into state-of-the-art meta learning algorithms such as MAML, Reptile, and CAML. You will then explore how to learn quickly with Meta-SGD and discover how you can perform unsupervised learning using meta learning with CACTUs. In the concluding chapters, you will work through recent trends in meta learning such as adversarial meta learning, task agnostic meta learning, and meta imitation learning.By the end of this book, you will be familiar with state-of-the-art meta learning algorithms and able to enable human-like cognition for your machine learning models.

React Design Patterns and Best Practices. Build easy to scale modular applications using the most powerful components and design patterns

Michele Bertoli

Taking a complete journey through the most valuable design patterns in React, this book demonstrates how to apply design patterns and best practices in real-life situations, whether that’s for new or already existing projects. It will help you to make your applications more flexible, perform better, and easier to maintain – giving your workflow a huge boost when it comes to speed without reducing quality. We’ll begin by understanding the internals of React before gradually moving on to writing clean and maintainable code. We’ll build components that are reusable across the application, structure applications, and create forms that actually work.Then we’ll style React components and optimize them to make applications faster and more responsive. Finally, we’ll write tests effectively and you’ll learn how to contribute to React and its ecosystem.By the end of the book, you’ll be saved from a lot of trial and error and developmental headaches, and you will be on the road to becoming a React expert.