Augmented Reality with Kinect. If you know C/C++ programming, then this book will give you the ability to develop augmented reality applications with Microsoft's Kinect. By the end of the course you will have created a complete game

Rui Wang

Microsoft Kinect changes the notion of user interface design. It differs from most other user input controllers as it enables users to interact with the program without touching the mouse or a trackpad. It utilizes motion sensing technology and all it needs is a real-time cameras, tracked skeletons, and gestures.Augmented Reality with Kinect will help you get into the world of Microsoft Kinect programming with the C/C++ language. The book will cover the installation, image streaming, skeleton and face tracking, multi-touch cursors and gesture emulation. Finally, you will end up with a complete Kinect-based game.Augmented Reality with Kinect will help you get into the world of Kinect programming, with a few interesting recipes and a relatively complete example. The book will introduce the following topics: the installation and initialization of Kinect applications; capturing color and depth images; obtaining skeleton and face tracking data; emulating multi-touch cursors and gestures; and developing a complete game using Kinect features.The book is divided in such a way so as to ensure that each topic is given the right amount of focus. Beginners will start from the first chapter and build up to developing their own applications.

Solr Cookbook. Solve real-time problems related to Apache Solr 4.x and 5.0 effectively with the help of over 100 easy-to-follow recipes

Rafal Kuc

Web Development with Blazor. A practical guide to start building interactive UIs with C# 11 and .NET 7 - Second Edition

Jimmy Engström, Jeff Fritz

Blazor is an essential tool if you want to build interactive web apps without JavaScript, but it has a learning curve. Updated with the latest code in .NET 7 and C# 11 and written by someone who adopted Blazor early, this book will help you overcome the challenges associated with being a beginner with Blazor and teach you the best coding practices.You’ll start by learning how to leverage the power of Blazor and exploring the full capabilities of both Blazor Server and Blazor WebAssembly. Then you'll move on to the practical part, centered around a sample project – a blog engine. You'll apply all your newfound knowledge about creating Blazor projects, the inner workings of Razor syntax, validating forms, and creating your own components.This new edition also looks at source generators, dives deeper into Blazor WebAssembly with ahead-of-time, and includes a dedicated new chapter demonstrating how to move components of an existing JavaScript (Angular, React) or MVC-based website to Blazor or combine the two. You’ll also see how to use Blazor (Hybrid) together with .NET MAUI to create cross-platform desktop and mobile applications.When you reach the end of this book, you'll have the confidence you need to create and deploy production-ready Blazor applications, and you'll have a big-picture view of the Blazor landscape.

The Statistics and Machine Learning with R Workshop. Unlock the power of efficient data science modeling with this hands-on guide

Liu Peng

The Statistics and Machine Learning with R Workshop is a comprehensive resource packed with insights into statistics and machine learning, along with a deep dive into R libraries. The learning experience is further enhanced by practical examples and hands-on exercises that provide explanations of key concepts.Starting with the fundamentals, you’ll explore the complete model development process, covering everything from data pre-processing to model development. In addition to machine learning, you’ll also delve into R's statistical capabilities, learning to manipulate various data types and tackle complex mathematical challenges from algebra and calculus to probability and Bayesian statistics. You’ll discover linear regression techniques and more advanced statistical methodologies to hone your skills and advance your career.By the end of this book, you'll have a robust foundational understanding of statistics and machine learning. You’ll also be proficient in using R's extensive libraries for tasks such as data processing and model training and be well-equipped to leverage the full potential of R in your future projects.

Data Modeling with Snowflake. A practical guide to accelerating Snowflake development using universal data modeling techniques

Serge Gershkovich, Kent Graziano

The Snowflake Data Cloud is one of the fastest-growing platforms for data warehousing and application workloads. Snowflake's scalable, cloud-native architecture and expansive set of features and objects enables you to deliver data solutions quicker than ever before.Yet, we must ensure that these solutions are developed using recommended design patterns and accompanied by documentation that’s easily accessible to everyone in the organization.This book will help you get familiar with simple and practical data modeling frameworks that accelerate agile design and evolve with the project from concept to code. These universal principles have helped guide database design for decades, and this book pairs them with unique Snowflake-native objects and examples like never before – giving you a two-for-one crash course in theory as well as direct application.By the end of this Snowflake book, you’ll have learned how to leverage Snowflake’s innovative features, such as time travel, zero-copy cloning, and change-data-capture, to create cost-effective, efficient designs through time-tested modeling principles that are easily digestible when coupled with real-world examples.

Getting Started with Red Hat Enterprise Virtualization. Leverage powerful Red Hat Enterprise Virtualization solutions to build your own IaaS cloud

Pradeep Subramaniaan

Python Reinforcement Learning. Solve complex real-world problems by mastering reinforcement learning algorithms using OpenAI Gym and TensorFlow

Sudharsan Ravichandiran, Sean Saito, Rajalingappaa Shanmugamani, Yang Wenzhuo

Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. This Learning Path will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms.The Learning Path starts with an introduction to RL followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. You'll also work on various datasets including image, text, and video. This example-rich guide will introduce you to deep RL algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore TensorFlow and OpenAI Gym to implement algorithms that also predict stock prices, generate natural language, and even build other neural networks. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many of the recent advancements in RL.By the end of the Learning Path, you will have all the knowledge and experience needed to implement RL and deep RL in your projects, and you enter the world of artificial intelligence to solve various real-life problems.This Learning Path includes content from the following Packt products:• Hands-On Reinforcement Learning with Python by Sudharsan Ravichandiran• Python Reinforcement Learning Projects by Sean Saito, Yang Wenzhuo, and Rajalingappaa Shanmugamani

Software Test Design. Write comprehensive test plans to uncover critical bugs in web, desktop, and mobile apps

Simon Amey

Software Test Design details best practices for testing software applications and writing comprehensive test plans. Written by an expert with over twenty years of experience in the high-tech industry, this guide will provide you with training and practical examples to improve your testing skills.Thorough testing requires a thorough understanding of the functionality under test, informed by exploratory testing and described by a detailed functional specification. This book is divided into three sections, the first of which will describe how best to complete those tasks to start testing from a solid foundation.Armed with the feature specification, functional testing verifies the visible behavior of features by identifying equivalence partitions, boundary values, and other key test conditions. This section explores techniques such as black- and white-box testing, trying error cases, finding security weaknesses, improving the user experience, and how to maintain your product in the long term.The final section describes how best to test the limits of your application. How does it behave under failure conditions and can it recover? What is the maximum load it can sustain? And how does it respond when overloaded?By the end of this book, you will know how to write detailed test plans to improve the quality of your software applications.