NetworkX is a leading free and open source package used for network science with the Python programming language. NetworkX can track properties of individuals and relationships, find communities, analyze resilience, detect key network locations, and perform a wide range of important tasks. With the recent release of version 2, NetworkX has been updated to be more powerful and easy to use.If you’re a data scientist, engineer, or computational social scientist, this book will guide you in using the Python programming language to gain insights into real-world networks. Starting with the fundamentals, you’ll be introduced to the core concepts of network science, along with examples that use real-world data and Python code. This book will introduce you to theoretical concepts such as scale-free and small-world networks, centrality measures, and agent-based modeling. You’ll also be able to look for scale-free networks in real data and visualize a network using circular, directed, and shell layouts.By the end of this book, you’ll be able to choose appropriate network representations, use NetworkX to build and characterize networks, and uncover insights while working with real-world systems.

PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power. This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders. You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text.By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease.

Machine learning is an essential part of today's data-driven world and is extensively used across industries, including financial forecasting, robotics, and web technology. This book will teach you how to efficiently develop machine learning applications in Go.The book starts with an introduction to machine learning and its development process, explaining the types of problems that it aims to solve and the solutions it offers. It then covers setting up a frictionless Go development environment, including running Go interactively with Jupyter notebooks. Finally, common data processing techniques are introduced.The book then teaches the reader about supervised and unsupervised learning techniques through worked examples that include the implementation of evaluation metrics. These worked examples make use of the prominent open-source libraries GoML and Gonum.The book also teaches readers how to load a pre-trained model and use it to make predictions. It then moves on to the operational side of running machine learning applications: deployment, Continuous Integration, and helpful advice for effective logging and monitoring.At the end of the book, readers will learn how to set up a machine learning project for success, formulating realistic success criteria and accurately translating business requirements into technical ones.

Jira is an issue tracker and project management system. With their latest release, the Jira team has now expanded their user base to agile teams as well as business teams. This book provides a comprehensive explanation covering all major components of Jira, including Jira Software, Jira Core, and Jira Service Desk.This book starts with an introduction to Jira's unique features and how it can be used as an issue-tracking tool. It will then teach you about how a new project is created by a Jira administrator, what responsibilities there are, and using correct and relevant schemes in your project. You will then learn how to configure project workflows and fields for project screens.You will understand the various permissions used in projects and the importance of project roles in Jira. Then, the book talks about the concepts of versions acting as milestones and using components when handling issues in your projects. It will then focus on analysing data using built-in reports and creating dashboards in Jira. At the end, it will discuss various best practices for users as well as project managers or project administrators.

Lua is a small, powerful and extendable scripting/programming language that can be used for learning to program, and writing games and applications, or as an embedded scripting language. There are many popular commercial projects that allow you to modify or extend them through Lua scripting, and this book will get you ready for that. This book is the easiest way to learn Lua. It introduces you to the basics of Lua and helps you to understand the problems it solves. You will work with the basic language features, the libraries Lua provides, and powerful topics such as object-oriented programming. Every aspect of programming in Lua, variables, data types, functions, tables, arrays and objects, is covered in sufficient detail for you to get started. You will also find out about Lua's module system and how to interface with the operating system.After reading this book, you will be ready to use Lua as a programming language to write code that can interface with the operating system, automate tasks, make playable games, and much more. This book is a solid starting point for those who want to learn Lua in order to move onto other technologies such as Love2D or Roblox.A quick start guide is a focused, shorter title that provides a faster paced introduction to a technology. It is designed for people who don't need all the details at this point in their learning curve. This presentation has been streamlined to concentrate on the things you really need to know.

Python's standard unittest module is based on the xUnit family of frameworks, which has its origins in Smalltalk and Java, and tends to be verbose to use and not easily extensible.The pytest framework on the other hand is very simple to get started, but powerful enough to cover complex testing integration scenarios, being considered by many the true Pythonic approach to testing in Python.In this book, you will learn how to get started right away and get the most out of pytest in your daily workflow, exploring powerful mechanisms and plugins to facilitate many common testing tasks. You will also see how to use pytest in existing unittest-based test suites and will learn some tricks to make the jump to a pytest-style test suite quickly and easily.

Blender is open source 3D creation software. With a long history and an enthusiastic community of users, it is the ideal choice for almost any kind of work with 3D modeling or animation. However, for new users, its power and flexibillity can sometimes be daunting, and that’s when you need this book!The book starts by showing you round the all-new Blender 2.8 user interface. You'll look at the most commonly-used options and tools, such as navigating in 3D and selecting objects. You will then use and manipulate one of the most important windows of the interface, the 3D View.You'll learn how to use essential tools for working with 3D modeling. To give your models the feel of real-world objects, you'll learn how to create materials and set up surfaces. You'll see how to use Physically-Based Rendering (PBR), which allows you to craft realistic surfaces such as wood, stone, and metal. You will also work with Eevee, a new real-time render engine in Blender. You will see how to add motion to objects, making use of Blender's impressive 3D animation features. Finally, you'll learn how to create scenes and organize them for rendering, and later add titles and effects using built-in Blender tools.By the end of the book, you will be able to use Blender 2.8 new UI, Create 3D Models with textures, Animations, and Render them in real-time using Eevee.

Blockchain is a technology that powers the development of decentralized applications.This technology allows the construction of a network with no single control that enables participants to make contributions to and receive benefits from the network directly.This book will give you a thorough overview of blockchain and explain how a blockchain works.You will begin by going through various blockchain consensus mechanisms and cryptographic hash functions. You will then learn the fundamentals of programming in Solidity – the defacto language for developing decentralize, applications in Ethereum. After that, you will set up an Ethereum development environment and develop, package, build, and test campaign-decentralized applications.The book also shows you how to set up Hyperledger composer tools, analyze business scenarios, design business models, and write a chain code. Finally, you will get a glimpse of how blockchain is actually used in different real-world domains. By the end of this guide, you will be comfortable working with basic blockchain frameworks, and develop secure, decentralized applications in a hassle-free manner.

Docker is an open source software platform that helps you with creating, deploying, and running your applications using containers. This book is your ideal introduction to Docker and containerization.You will learn how to set up a Docker development environment on a Linux, Mac, or Windows workstation, and learn your way around all the commands to run and manage your Docker images and containers.You will explore the Dockerfile and learn how to build your own enterprise-grade Docker images. Then you will learn about Docker networks, Docker swarm, and Docker volumes, and how to use these features with Docker stacks in order to define, deploy, and maintain highly-scalable, fault-tolerant multi-container applications.Finally, you will learn how to leverage Docker with Jenkins to automate the building of Docker images and the deployment of Docker containers. By the end of this book, you will be well prepared when it comes to using Docker for your next project.

Python's standard unittest module is based on the xUnit family of frameworks, which has its origins in Smalltalk and Java, and tends to be verbose to use and not easily extensible.The pytest framework on the other hand is very simple to get started, but powerful enough to cover complex testing integration scenarios, being considered by many the true Pythonic approach to testing in Python.In this book, you will learn how to get started right away and get the most out of pytest in your daily workflow, exploring powerful mechanisms and plugins to facilitate many common testing tasks. You will also see how to use pytest in existing unittest-based test suites and will learn some tricks to make the jump to a pytest-style test suite quickly and easily.