Blockchain for Decision Makers. A systematic guide to using blockchain for improving your business

Romain Tormen

In addition to cryptocurrencies, blockchain-based apps are being developed in different industries such as banking, supply chain, and healthcare to achieve digital transformation and enhance user experience. Blockchain is not only about Bitcoin or cryptocurrencies, but also about different technologies such as peer-to-peer networks, consensus mechanisms, and cryptography. These technologies together help sustain trustless environments in which digital value can be transferred between individuals without intermediaries.This book will help you understand the basics of blockchain such as consensus protocols, decentralized applications, and tokenization. You'll focus on how blockchain is used today in different industries and the technological challenges faced while implementing a blockchain strategy. The book also enables you, as a decision maker, to understand blockchain from a technical perspective and evaluate its applicability in your business. Finally, you'll get to grips with blockchain frameworks such as Hyperledger and Quorum and their usability.By the end of this book, you'll have learned about the current use cases of blockchain and be able to implement a blockchain strategy on your own.

Machine Learning on Kubernetes. A practical handbook for building and using a complete open source machine learning platform on Kubernetes

Faisal Masood, Ross Brigoli

MLOps is an emerging field that aims to bring repeatability, automation, and standardization of the software engineering domain to data science and machine learning engineering. By implementing MLOps with Kubernetes, data scientists, IT professionals, and data engineers can collaborate and build machine learning solutions that deliver business value for their organization.You'll begin by understanding the different components of a machine learning project. Then, you'll design and build a practical end-to-end machine learning project using open source software. As you progress, you'll understand the basics of MLOps and the value it can bring to machine learning projects. You will also gain experience in building, configuring, and using an open source, containerized machine learning platform. In later chapters, you will prepare data, build and deploy machine learning models, and automate workflow tasks using the same platform. Finally, the exercises in this book will help you get hands-on experience in Kubernetes and open source tools, such as JupyterHub, MLflow, and Airflow.By the end of this book, you'll have learned how to effectively build, train, and deploy a machine learning model using the machine learning platform you built.

Unity 2020 By Example. A project-based guide to building 2D, 3D, augmented reality, and virtual reality games from scratch - Third Edition

Robert Wells

The Unity game engine, used by millions of developers around the world, is popular thanks to its features that enable you to create games and 3D apps for desktop and mobile platforms in no time. With Unity 2020, this state-of-the-art game engine introduces enhancements in Unity tooling, editor, and workflow, among many other additions.The third edition of this Unity book is updated to the new features in Unity 2020 and modern game development practices. Once you’ve quickly got to grips with the fundamentals of Unity game development, you’ll create a collection, a twin-stick shooter, and a 2D adventure game. You’ll then explore advanced topics such as machine learning, virtual reality, and augmented reality by building complete projects using the latest game tool kit. As you implement concepts in practice, this book will ensure that you come away with a clear understanding of Unity game development.By the end of the book, you'll have a firm foundation in Unity development using C#, which can be applied to other engines and programming languages. You'll also be able to create several real-world projects to add to your professional game development portfolio.

Electron Projects. Build over 9 cross-platform desktop applications from scratch

Denys Vuika

The Electron framework allows you to use modern web technologies to build applications that share the same code across all operating systems and platforms. This also helps designers to easily transition from the web to the desktop. Electron Projects guides you through building cross-platform Electron apps with modern web technologies and JavaScript frameworks such as Angular, React.js, and Vue.js.You’ll explore the process of configuring modern JavaScript frameworks and UI libraries, real-time analytics and automatic updates, and interactions with the operating system. You’ll get hands-on with building a basic Electron app, before moving on to implement a Markdown Editor. In addition to this, you’ll be able to experiment with major JavaScript frameworks such as Angular and Vue.js, discovering ways to integrate them with Electron apps for building cross-platform desktop apps. Later, you’ll learn to build a screenshot snipping tool, a mini-game, and a music player, while also gaining insights into analytics, bug tracking, and licensing. You’ll then get to grips with building a chat app, an eBook generator and finally a simple digital wallet app.By the end of this book, you’ll have experience in building a variety of projects and project templates that will help you to apply your knowledge when creating your own cross-platform applications.

Expert Python Programming. Become a master in Python by learning coding best practices and advanced programming concepts in Python 3.7 - Third Edition

Michał Jaworski, Tarek Ziadé

Python is a dynamic programming language that's used in a wide range of domains thanks to its simple yet powerful nature. Although writing Python code is easy, making it readable, reusable, and easy to maintain is challenging. Complete with best practices, useful tools, and standards implemented by professional Python developers, the third edition of Expert Python Programming will help you overcome this challenge.The book will start by taking you through the new features in Python 3.7. You'll then learn the advanced components of Python syntax, in addition to understanding how to apply concepts of various programming paradigms, including object-oriented programming, functional programming, and event-driven programming. This book will also guide you through learning the naming best practices, writing your own distributable Python packages, and getting up to speed with automated ways to deploy your software on remote servers. You’ll discover how to create useful Python extensions with C, C++, Cython, and CFFI. Furthermore, studying about code management tools, writing clear documentation, and exploring test-driven development will help you write clean code.By the end of the book, you will have become an expert in writing efficient and maintainable Python code.

Google Plus First Look: a tip-packed, comprehensive look at Google+. Get up and running with Google+ fast with this book and

Ralph Roberts

Big Data Analytics with R. Leverage R Programming to uncover hidden patterns in your Big Data

Simon Walkowiak

Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing.The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O.

Creative DIY Microcontroller Projects with TinyGo and WebAssembly. A practical guide to building embedded applications for low-powered devices, IoT, and home automation

Tobias Theel

While often considered a fast and compact programming language, Go usually creates large executables that are difficult to run on low-memory or low-powered devices such as microcontrollers or IoT. TinyGo is a new compiler that allows developers to compile their programs for such low-powered devices. As TinyGo supports all the standard features of the Go programming language, you won't have to tweak the code to fit on the microcontroller.This book is a hands-on guide packed full of interesting DIY projects that will show you how to build embedded applications. You will learn how to program sensors and work with microcontrollers such as Arduino UNO and Arduino Nano IoT 33. The chapters that follow will show you how to develop multiple real-world embedded projects using a variety of popular devices such as LEDs, 7-segment displays, and timers. Next, you will progress to build interactive prototypes such as a traffic lights system, touchless hand wash timer, and more. As you advance, you'll create an IoT prototype of a weather alert system and display those alerts on the TinyGo WASM dashboard. Finally, you will build a home automation project that displays stats on the TinyGo WASM dashboard.By the end of this microcontroller book, you will be equipped with the skills you need to build real-world embedded projects using the power of TinyGo.