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BeagleBone Blue is effectively a small, light, cheap computer in a similar vein to Raspberry Pi and Arduino. It has all of the extensibility of today’s desktop machines, but without the bulk, expense, or noise. This project guide provides step-by-step instructions that enable anyone to use this new, low-cost platform in some fascinating robotics projects. By the time you are finished, your projects will be able to see, speak, listen,detect their surroundings, and move in a variety of amazing ways.The book begins with unpacking and powering up the components. This includes guidance on what to purchase and how to connect it all successfully, and a primer on programming the BeagleBone Blue. You will add additional software functionality available from the open source community, including making the system see using a webcam, hear using a microphone, and speak using a speaker.You will then learn to use the new hardware capability of the BeagleBone Blue to make your robots move, as well as discover how to add sonar sensors to avoid or find objects. Later, you will learn to remotelycontrol your robot through iOS and Android devices. At the end of this book, you will seehow to integrate all of these functionalities to work together, before developing the most impressive robotics projects: Drone and Submarine.
The Modern C# Challenge. Become an expert C# programmer by solving interesting programming problems
C# is a multi-paradigm programming language. The Modern C# Challenge covers with aspects of the .NET Framework such as the Task Parallel Library (TPL) and CryptoAPI. It also encourages you to explore important programming trade-offs such as time versus space or simplicity. There may be many ways to solve a problem and there is often no single right way, but some solutions are definitely better than others. This book has combined these solutions to help you solve real-world problems with C#.In addition to describing programming trade-offs, The Modern C# Challenge will help you build a useful toolkit of techniques such as value caching, statistical analysis, and geometric algorithms.By the end of this book, you will have walked through challenges in C# and explored the .NET Framework in order to develop program logic for real-world applications.
KVM Virtualization Cookbook. Learn how to use KVM effectively in production
Virtualization technologies such as KVM allow for better control over the available server resources, by deploying multiple virtual instances on the same physical host, or clusters of compute resources. With KVM it is possible to run various workloads in isolation with the hypervisor layer providing better tenant isolation and higher degree of security. This book will provide a deep dive into deploying KVM virtual machines using qemu and libvirt and will demonstrate practical examples on how to run, scale, monitor, migrate and backup such instances. You will also discover real production ready recipes on deploying KVM instances with OpenStack and how to programatically manage the life cycle of KVM virtual machines using Python. You will learn numerous tips and techniques which will help you deploy & plan the KVM infrastructure. Next, you will be introduced to the working of libvirt libraries and the iPython development environment. Finally, you will be able to tune your Linux kernel for high throughput and better performance. By the end of this book, you will gain all the knowledge needed to be an expert in working with the KVM virtualization infrastructure.
Physics is really important for game programmers who want to add realism and functionality to their games. Collision detection in particular is a problem that affects all game developers, regardless of the platform, engine, or toolkit they use.This book will teach you the concepts and formulas behind collision detection. You will also be taught how to build a simple physics engine, where Rigid Body physics is the main focus, and learn about intersection algorithms for primitive shapes.You’ll begin by building a strong foundation in mathematics that will be used throughout the book. We’ll guide you through implementing 2D and 3D primitives and show you how to perform effective collision tests for them. We then pivot to one of the harder areas of game development—collision detection and resolution. Further on, you will learn what a Physics engine is, how to set up a game window, and how to implement rendering. We’ll explore advanced physics topics such as constraint solving. You’ll also find out how to implement a rudimentary physics engine, which you can use to build an Angry Birds type of game or a more advanced game.By the end of the book, you will have implemented all primitive and some advanced collision tests, and you will be able to read on geometry and linear Algebra formulas to take forward to your own games!
This book is a detailed IT Asset Management (ITAM) guidebook with real-world templates that can be converted into working ITAM documents. It is a step-by-step IT Asset Management manual for the newbies as well as the seasoned ITAM veterans, providing a unique insight into asset management. It discusses how risk management has changed over time and the possible solutions needed to address the new normal. This book is your perfect guide to create holistic IT Asset Management and Software Asset Management programs that close the risk gaps, increases productivity and results in cost efficiencies. It allows the IT Asset Managers, Software Asset Managers, and/or the full ITAM program team to take a deep dive by using the templates offered in the guidebook. You will be aware of the specific roles and responsibilities for every aspect of IT Asset Management, Software Asset Management, and Software License Compliance Audit Response. By the end of this book, you will be well aware of what IT and Software Asset Management is all about and the different steps, processes, and roles required to truly master it.
Getting started with data science doesn't have to be an uphill battle. Applied Data Science with Python and Jupyter is a step-by-step guide ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction to these concepts. In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques. You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations.
IBM Watson provides fast, intelligent insight in ways that the human brain simply can't match. Through eight varied projects, this book will help you explore the computing and analytical capabilities of IBM Watson.The book begins by refreshing your knowledge of IBM Watson's basic data preparation capabilities, such as adding and exploring data to prepare it for being applied to models. The projects covered in this book can be developed for different industries, including banking, healthcare, media, and security. These projects will enable you to develop an AI mindset and guide you in developing smart data-driven projects, including automating supply chains, analyzing sentiment in social media datasets, and developing personalized recommendations.By the end of this book, you'll have learned how to develop solutions for process automation, and you'll be able to make better data-driven decisions to deliver an excellent customer experience.
Ankit Jain, Armando Fandango, Amita Kapoor
TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits—simplicity, efficiency, and flexibility—of using TensorFlow in various real-world projects. With the help of this book, you’ll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem.To start with, you’ll get to grips with using TensorFlow for machine learning projects; you’ll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification.As you make your way through the book, you’ll build projects in various real-world domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative Adversarial Networks (GANs), capsule networks, and reinforcement learning. You’ll learn how to use the TensorFlow on Spark API and GPU-accelerated computing with TensorFlow to detect objects, followed by how to train and develop a recurrent neural network (RNN) model to generate book scripts.By the end of this book, you’ll have gained the required expertise to build full-fledged machine learning projects at work.