Learn the art of making Android games and turn your game development dreams into reality About This Book ? Leverage the latest features of Android N to create real-world 2D games ? Architect a 2D game from scratch and level up your Android game development skill ? Transition from developing simple 2D games to 3D games using basic Java code Who This Book Is For If you are a mobile developer who has basic Java programming knowledge, then this book is ideal for you. Previous Android development experience is not needed; however, basic mobile development knowledge is essential. What You Will Learn ? Understand the nuts and bolts of developing highly interactive and interesting games for Android N ? Link the interface to the code used in games through simple methods ? Interact with the images on the screen and also learn to animate them ? Set and save the game state and save high scores, hit points, and so on for your games ? Get a grasp of various collision techniques and implement the bounding box technique ? Convert your 2D games to 3D games using Android N ? Get an understanding of the process of UI creation using Android Studio In Detail In this book, we’ll start with installing Android studio and its components, and setting it up ready for Android N. We teach you how to take inputs from users, create images and interact with them, and work with sprites to create animations. You’ll then explore the various collision detection methods and use sprites to create an explosion. Moving on, you’ll go through the process of UI creation and see how to create buttons as well as display the score and other parameters on screen. By the end of the book, you will have a working example and an understanding of a 2D platform game like Super Mario and know how to convert your 2D games to 3D games. Style and approach This easy-to-understand guide follows a step-by-step approach to building games, and contains plenty of graphical examples for you to follow and grasp quickly, giving you the chance to implement the concepts practically.

Successfully scrape data from any website with the power of Python 3.x About This Book ? A hands-on guide to web scraping using Python with solutions to real-world problems ? Create a number of different web scrapers in Python to extract information ? This book includes practical examples on using the popular and well-maintained libraries in Python for your web scraping needs Who This Book Is For This book is aimed at developers who want to use web scraping for legitimate purposes. Prior programming experience with Python would be useful but not essential. Anyone with general knowledge of programming languages should be able to pick up the book and understand the principals involved. What You Will Learn ? Extract data from web pages with simple Python programming ? Build a concurrent crawler to process web pages in parallel ? Follow links to crawl a website ? Extract features from the HTML ? Cache downloaded HTML for reuse ? Compare concurrent models to determine the fastest crawler ? Find out how to parse JavaScript-dependent websites ? Interact with forms and sessions In Detail The Internet contains the most useful set of data ever assembled, most of which is publicly accessible for free. However, this data is not easily usable. It is embedded within the structure and style of websites and needs to be carefully extracted. Web scraping is becoming increasingly useful as a means to gather and make sense of the wealth of information available online. This book is the ultimate guide to using the latest features of Python 3.x to scrape data from websites. In the early chapters, you’ll see how to extract data from static web pages. You’ll learn to use caching with databases and files to save time and manage the load on servers. After covering the basics, you’ll get hands-on practice building a more sophisticated crawler using browsers, crawlers, and concurrent scrapers. You’ll determine when and how to scrape data from a JavaScript-dependent website using PyQt and Selenium. You’ll get a better understanding of how to submit forms on complex websites protected by CAPTCHA. You’ll find out how to automate these actions with Python packages such as mechanize. You’ll also learn how to create class-based scrapers with Scrapy libraries and implement your learning on real websites. By the end of the book, you will have explored testing websites with scrapers, remote scraping, best practices, working with images, and many other relevant topics. Style and approach This hands-on guide is full of real-life examples and solutions starting simple and then progressively becoming more complex. Each chapter in this book introduces a problem and then provides one or more possible solutions.

Simplify real-time data processing by leveraging the power of Apache Kafka 1.0 About This Book ? Use Kafka 1.0 features such as Confluent platforms and Kafka streams to build efficient streaming data applications to handle and process your data ? Integrate Kafka with other Big Data tools such as Apache Hadoop, Apache Spark, and more ? Hands-on recipes to help you design, operate, maintain, and secure your Apache Kafka cluster with ease Who This Book Is For This book is for developers and Kafka administrators who are looking for quick, practical solutions to problems encountered while operating, managing or monitoring Apache Kafka. If you are a developer, some knowledge of Scala or Java will help, while for administrators, some working knowledge of Kafka will be useful. What You Will Learn ? Install and configure Apache Kafka 1.0 to get optimal performance ? Create and configure Kafka Producers and Consumers ? Operate your Kafka clusters efficiently by implementing the mirroring technique ? Work with the new Confluent platform and Kafka streams, and achieve high availability with Kafka ? Monitor Kafka using tools such as Graphite and Ganglia ? Integrate Kafka with third-party tools such as Elasticsearch, Logstash, Apache Hadoop, Apache Spark, and more In Detail Apache Kafka provides a unified, high-throughput, low-latency platform to handle real-time data feeds. This book will show you how to use Kafka efficiently, and contains practical solutions to the common problems that developers and administrators usually face while working with it. This practical guide contains easy-to-follow recipes to help you set up, configure, and use Apache Kafka in the best possible manner. You will use Apache Kafka Consumers and Producers to build effective real-time streaming applications. The book covers the recently released Kafka version 1.0, the Confluent Platform and Kafka Streams. The programming aspect covered in the book will teach you how to perform important tasks such as message validation, enrichment and composition.Recipes focusing on optimizing the performance of your Kafka cluster, and integrate Kafka with a variety of third-party tools such as Apache Hadoop, Apache Spark, and Elasticsearch will help ease your day to day collaboration with Kafka greatly. Finally, we cover tasks related to monitoring and securing your Apache Kafka cluster using tools such as Ganglia and Graphite. If you're looking to become the go-to person in your organization when it comes to working with Apache Kafka, this book is the only resource you need to have. Style and approach Following a cookbook recipe-based approach, we’ll teach you how to solve everyday difficulties and struggles you encounter using Kafka through hands-on examples.

Deliver end-to-end real-time distributed data processing solutions by leveraging the power of Elastic Stack 6.0 About This Book ? Get to grips with the new features introduced in Elastic Stack 6.0 ? Get valuable insights from your data by working with the different components of the Elastic stack such as Elasticsearch, Logstash, Kibana, X-Pack, and Beats ? Includes handy tips and techniques to build, deploy and manage your Elastic applications efficiently on-premise or on the cloud Who This Book Is For This book is for data professionals who want to get amazing insights and business metrics from their data sources. If you want to get a fundamental understanding of the Elastic Stack for distributed, real-time processing of data, this book will help you. A fundamental knowledge of JSON would be useful, but is not mandatory. No previous experience with the Elastic Stack is required. What You Will Learn ? Familiarize yourself with the different components of the Elastic Stack ? Get to know the new functionalities introduced in Elastic Stack 6.0 ? Effectively build your data pipeline to get data from terabytes or petabytes of data into Elasticsearch and Logstash for searching and logging ? Use Kibana to visualize data and tell data stories in real-time ? Secure, monitor, and use the alerting and reporting capabilities of Elastic Stack ? Take your Elastic application to an on-premise or cloud-based production environment In Detail The Elastic Stack is a powerful combination of tools for distributed search, analytics, logging, and visualization of data from medium to massive data sets. The newly released Elastic Stack 6.0 brings new features and capabilities that empower users to find unique, actionable insights through these techniques. This book will give you a fundamental understanding of what the stack is all about, and how to use it efficiently to build powerful real-time data processing applications. After a quick overview of the newly introduced features in Elastic Stack 6.0, you’ll learn how to set up the stack by installing the tools, and see their basic configurations. Then it shows you how to use Elasticsearch for distributed searching and analytics, along with Logstash for logging, and Kibana for data visualization. It also demonstrates the creation of custom plugins using Kibana and Beats. You’ll find out about Elastic X-Pack, a useful extension for effective security and monitoring. We also provide useful tips on how to use the Elastic Cloud and deploy the Elastic Stack in production environments. On completing this book, you’ll have a solid foundational knowledge of the basic Elastic Stack functionalities. You’ll also have a good understanding of the role of each component in the stack to solve different data processing problems. Style and approach This step-by-step guide will show you the Elastic Stack, covering all the components through interactive and easy-to-follow examples. It also includes handy tips.

Learn to distribute network traffic, optimize application delivery, and defend network-level threats. Key Features * Quickly get up and running with Azure networking solutions * Level-up your cloud networking skills by planning, implementing, configuring, and securing your infrastructure network with Azure * Leverage Azure networking services to provide applications highly available and fault tolerant environment Book Description Microsoft provides organizations with an effective way of managing their network with Azure's networking services. No matter the size of your organization, Azure provides a way to highly reliable performance and secure connectivity with its networking services. The book starts with an introduction to the Azure networking like creating Azure virtual networks, designing address spaces and subnets. Then you will learn to create and manage network security groups, application security groups, and IP addresses in Azure. Gradually, we move on to various aspects like S2S, P2S, and Vnet2Vnet connections, DNS and routing, load balancers and traffic manager. This book will cover every aspect and function required to deliver practical recipes to help readers learn from basic cloud networking practices to planning, implementing, and securing their infrastructure network with Azure. Readers will not only be able to upscale their current environment but will also learn to monitor, diagnose, and ensure secure connectivity. After learning to deliver a robust environment readers will also gain meaningful insights from recipes on best practices. By the end of this book, readers will gain hands-on experience in providing cost-effective solutions that benefit organizations. What you will learn * Learn to create Azure networking services * Understand how to create and work on hybrid connections * Configure and manage Azure network services * Learn ways to design high availability network solutions in Azure * Discover how to monitor and troubleshoot Azure network resources * Learn different methods of connecting local networks to Azure virtual networks Who this book is for This book is targeted towards cloud architects, cloud solution providers, or any stakeholders dealing with networking on the Azure cloud. Some prior understanding of Microsoft Azure will be a plus point.

Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch Key Features * Learn and implement machine learning algorithms in a variety of real-life scenarios * Cover a range of tasks catering to supervised, unsupervised and reinforcement learning techniques * Find easy-to-follow code solutions for tackling common and not-so-common challenges Book Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks. With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples. What you will learn * Use predictive modeling and apply it to real-world problems * Explore data visualization techniques to interact with your data * Learn how to build a recommendation engine * Understand how to interact with text data and build models to analyze it * Work with speech data and recognize spoken words using Hidden Markov Models * Get well versed with reinforcement learning, automated ML, and transfer learning * Work with image data and build systems for image recognition and biometric face recognition * Use deep neural networks to build an optical character recognition system Who this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is what you need. Familiarity with Python programming and machine learning concepts will be useful.

Test your C++ programming skills by solving real-world programming problems covered in the book About This Book ? Solve a variety of real-world programming and logic problems by leveraging the power of C++17 ? Test your skills in using language features, algorithms, data structures, design patterns, and more ? Explore areas such as cryptography, communication, and image handling in C++ Who This Book Is For This book will appeal to C++ developers of all levels. There's a challenge inside for everyone. What You Will Learn ? Serialize and deserialize JSON and XML data ? Perform encryption and signing to facilitate secure communication between parties ? Embed and use SQLite databases in your applications ? Use threads and asynchronous functions to implement generic purpose parallel algorithms ? Compress and decompress files to/from a ZIP archive ? Implement data structures such as circular buffer and priority queue ? Implement general purpose algorithms as well as algorithms that solve specific problems ? Create client-server applications that communicate over TCP/IP ? Consume HTTP REST services ? Use design patterns to solve real-world problems In Detail C++ is one of the most widely-used programming languages and has applications in a variety of fields, such as gaming, GUI programming, and operating systems, to name a few. Through the years, C++ has evolved into (and remains) one of the top choices for software developers worldwide. This book will show you some notable C++ features and how to implement them to meet your application needs. Each problem is unique and doesn't just test your knowledge of the language; it tests your ability to think out of the box and come up with the best solutions. With varying levels of difficulty, you'll be faced with a wide variety of challenges. And in case you're stumped, you don't have to worry: we've got the best solutions to the problems in the book. So are you up for the challenge? Style and approach A recipe-based approach where each problem is solved with the help of step by step instructions.

Enhance the power of NumPy and start boosting your scientific computing capabilities About This Book ? Grasp all aspects of numerical computing and understand NumPy ? Explore examples to learn exploratory data analysis (EDA), regression, and clustering ? Access NumPy libraries and use performance benchmarking to select the right tool Who This Book Is For Mastering Numerical Computing with NumPy is for you if you are a Python programmer, data analyst, data engineer, or a data science enthusiast, who wants to master the intricacies of NumPy and build solutions for your numeric and scientific computational problems. You are expected to have familiarity with mathematics to get the most out of this book. What You Will Learn ? Perform vector and matrix operations using NumPy ? Perform exploratory data analysis (EDA) on US housing data ? Develop a predictive model using simple and multiple linear regression ? Understand unsupervised learning and clustering algorithms with practical use cases ? Write better NumPy code and implement the algorithms from scratch ? Perform benchmark tests to choose the best configuration for your system In Detail NumPy is one of the most important scientific computing libraries available for Python. Mastering Numerical Computing with NumPy teaches you how to achieve expert level competency to perform complex operations, with in-depth coverage of advanced concepts. Beginning with NumPy's arrays and functions, you will familiarize yourself with linear algebra concepts to perform vector and matrix math operations. You will thoroughly understand and practice data processing, exploratory data analysis (EDA), and predictive modeling. You will then move on to working on practical examples which will teach you how to use NumPy statistics in order to explore US housing data and develop a predictive model using simple and multiple linear regression techniques. Once you have got to grips with the basics, you will explore unsupervised learning and clustering algorithms, followed by understanding how to write better NumPy code while keeping advanced considerations in mind. The book also demonstrates the use of different high-performance numerical computing libraries and their relationship with NumPy. You will study how to benchmark the performance of different configurations and choose the best for your system. By the end of this book, you will have become an expert in handling and performing complex data manipulations. Style and approach This mastering guide will help you master your skills required to perform a complex numerical computation. The book contains the right mixture of theory and practical examples that will help you in dealing with the advanced NumPy and build solutions for your numeric and scientific computational problems

A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python About This Book ? Your entry point into the world of artificial intelligence using the power of Python ? An example-rich guide to master various RL and DRL algorithms ? Explore various state-of-the-art architectures along with math Who This Book Is For If you’re a machine learning developer or deep learning enthusiast interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you. Some knowledge of linear algebra, calculus, and the Python programming language will help you understand the concepts covered in this book. What You Will Learn ? Understand the basics of reinforcement learning methods, algorithms, and elements ? Train an agent to walk using OpenAI Gym and Tensorflow ? Understand the Markov Decision Process, Bellman’s optimality, and TD learning ? Solve multi-armed-bandit problems using various algorithms ? Master deep learning algorithms, such as RNN, LSTM, and CNN with applications ? Build intelligent agents using the DRQN algorithm to play the Doom game ? Teach agents to play the Lunar Lander game using DDPG ? Train an agent to win a car racing game using dueling DQN In Detail Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. Hands-On Reinforcement learning with Python will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms. The book starts with an introduction to Reinforcement Learning followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms and concepts, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. This example-rich guide will introduce you to deep reinforcement learning algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many more of the recent advancements in reinforcement learning. By the end of the book, you will have all the knowledge and experience needed to implement reinforcement learning and deep reinforcement learning in your projects, and you will be all set to enter the world of artificial intelligence. Style and approach This is a hands-on book designed to further expand your machine learning skills by understanding reinforcement to deep reinforcement learning algorithms with applications in Python.

Unleash Python and take your small readers on an adventurous ride through the world of programming About This Book Learn to start using Python for some simple programming tasks such as doing easy mathematical calculations. Use logic and control loops to build a nice interesting game. Get to grips with working with data and, once you're comfortable with that, you'll be introduced to Pygame, which will help you wrap up the book with a cool game. Who This Book Is For This book is for kids (aged 10 and over). This is book is intended for absolute beginners who lack any knowledge of computing or programming languages and want to get started in the world of programming. What You Will Learn Start fiddling with Python's variables, build functions and interact with users Build your own calculator using the Math Library Train Python to make logical decisions Work with moving 2D objects on-screen Understand the Pygame Library and build your very own game! Write a cool program to manage inventories in your backpack In Detail Kids are always the most fast-paced and enthusiastic learners, and are naturally willing to build stuff that looks like magic at the end (when it works!). Programming can be one such magic. Being able to write a program that works helps them feel they've really achieved something. Kids today are very tech-savvy and cannot wait to enter the fast-paced digital world. Because Python is one of the most popular languages and has a syntax that is quite simple to understand, even kids are eager to use it as a stepping stone to learning programming languages. This book will cover projects that are simple and fun, and teach kids how to write Python code that works. The book will teach the basics of Python programming, installation, and so on and then will move on to projects. A total of three projects, with each and every step explained carefully, without any assumption of previous experience. Style and approach The book will take a light approach in guiding the little readers through the world of Python. The main idea is to teach by example and let the readers have as much exercises to do, so that they learn faster and can apply their own ideas to the existing examples. The book should get them thinking, by the end, on where they can go next with such a powerful tool at their disposal.

Harness the power of multiple computers using Python through this fast-paced informative guide About This Book You'll learn to write data processing programs in Python that are highly available, reliable, and fault tolerant Make use of Amazon Web Services along with Python to establish a powerful remote computation system Train Python to handle data-intensive and resource hungry applications Who This Book Is For This book is for Python developers who have developed Python programs for data processing and now want to learn how to write fast, efficient programs that perform CPU-intensive data processing tasks. What You Will Learn Get an introduction to parallel and distributed computing See synchronous and asynchronous programming Explore parallelism in Python Distributed application with Celery Python in the Cloud Python on an HPC cluster Test and debug distributed applications In Detail CPU-intensive data processing tasks have become crucial considering the complexity of the various big data applications that are used today. Reducing the CPU utilization per process is very important to improve the overall speed of applications. This book will teach you how to perform parallel execution of computations by distributing them across multiple processors in a single machine, thus improving the overall performance of a big data processing task. We will cover synchronous and asynchronous models, shared memory and file systems, communication between various processes, synchronization, and more. Style and Approach This example based, step-by-step guide will show you how to make the best of your hardware configuration using Python for distributing applications.

Explore the power of React components for cutting-edge web development About This Book Learn to build better websites by creating a variety of different components in React Conceptualize the design and build maintainable web apps with the help of components A fast-paced guide to help you learn about component-based development in React Who This Book Is For This book is ideal for developers who are familiar with the basics of React and are looking for a guide to building a wide range of components as well as develop component-driven UIs. What You Will Learn How to structure an app into components Working with nested components Work with nested components Set up communication across components Style the existing components Work with Material Design as a component Render components on the server Make the best of design patterns Make the app pluggable In Detail The reader will learn how to use React and its component-based architecture in order to develop modern user interfaces. A new holistic way of thinking about UI development will establish throughout this book and the reader will discover the power of React components with many examples. After reading the book and following the example application, the reader has built a small to a mid-size application with React using a component based UI architecture. The book will take the reader through a journey to discover the benefits of component-based user interfaces over the classical MVC architecture. Throughout the book, the reader will develop a wide range of components and then bring them together to build a component-based UI. By the end of this book, readers would have learned several techniques to build powerful components and how the component-based development is beneficial over regular web development. Style and approach This book is a compact, example-driven guide that provides a step-by-step approach.

Familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R About This Book Predict and use a probabilistic graphical models (PGM) as an expert system Comprehend how your computer can learn Bayesian modeling to solve real-world problems Know how to prepare data and feed the models by using the appropriate algorithms from the appropriate R package Who This Book Is For This book is for anyone who has to deal with lots of data and draw conclusions from it, especially when the data is noisy or uncertain. Data scientists, machine learning enthusiasts, engineers, and those who curious about the latest advances in machine learning will find PGM interesting. What You Will Learn Understand the concepts of PGM and which type of PGM to use for which problem Tune the model’s parameters and explore new models automatically Understand the basic principles of Bayesian models, from simple to advanced Transform the old linear regression model into a powerful probabilistic model Use standard industry models but with the power of PGM Understand the advanced models used throughout today's industry See how to compute posterior distribution with exact and approximate inference algorithms In Detail Probabilistic graphical models (PGM, also known as graphical models) are a marriage between probability theory and graph theory. Generally, PGMs use a graph-based representation. Two branches of graphical representations of distributions are commonly used, namely Bayesian networks and Markov networks. R has many packages to implement graphical models. We’ll start by showing you how to transform a classical statistical model into a modern PGM and then look at how to do exact inference in graphical models. Proceeding, we’ll introduce you to many modern R packages that will help you to perform inference on the models. We will then run a Bayesian linear regression and you’ll see the advantage of going probabilistic when you want to do prediction. Next, you’ll master using R packages and implementing its techniques. Finally, you’ll be presented with machine learning applications that have a direct impact in many fields. Here, we’ll cover clustering and the discovery of hidden information in big data, as well as two important methods, PCA and ICA, to reduce the size of big problems. Style and approach This book gives you a detailed and step-by-step explanation of each mathematical concept, which will help you build and analyze your own machine learning models and apply them to real-world problems. The mathematics is kept simple and each formula is explained thoroughly.

If you are an iOS developer with experience in Objective-C, and wish to develop applications with Swift, then this book is ideal for you. Familiarity with the fundamentals of Swift is an added advantage but not a necessity.

This book is packed with real world examples that cover concepts and usability of the core modules of a complex application. If you are Project manager or consultant looking forward to using and implementing Oracle Primavera Contract Management in your organization, then this is the best guide for you. No prior knowledge of PCM required.

This is a hands-on book to quickly get you up to speed with SQL Server 2012. It covers all the new features of the core database engine as well as the business intelligence (BI) services.The book begins by taking you step-by-step through the installation process, showing you what to install and which services and features you need. Once you have your SQL Server in place, you learn how to administer it and then explore new T-SQL functions to expand your query-writing toolkit. You will discover how the enhancements to Integration Services, Analysis Services and Reporting Services make developing BI solutions easier. It will then introduce you to SQL Server Data Tools, your new and improved development environment for creating database and BI projects.A hands-on example guides you through the steps required to run Distributed Replay, giving you the experience you need to apply this in the field. The book then takes you through a detailed example to show you how to create a Data Quality Services project and cleanse real-world data. Easy to follow code samples provide you with the queries you need to set up Availability Groups using the new AlwaysOn technology.Once you are comfortable with these new features you will be ready to migrate your data to the cloud and into SQL Azure. An exploration of Hadoop will help you understand big data and how it really is the next big thing,This concise reference is for database administrators, SQL Server Developers and BI professionals. Anyone who is familiar with SQL Server 2008 R2 and needs to make the jump to the latest version with the shortest learning curve will find this book useful.

This book is for web developers willing to build better web applications. A basic knowledge of PHP, XML, JavaScript and MySQL, or a strong will to learn-as-you-type, is assumed.

The book is uniquely practical. A richly textured case study is used throughout the book. Although some aspects of the Airport Passenger Services business process are simplified for sake of clarity and efficiency, it provides a comprehensive practical grounding for theoretical UML knowledge. The case study itself was developed in partnership with employees of Zurich Airport. The book was written for business analysts, technical architects and developers. It does not require detailed programming knowledge, nor is prior experience of UML mandatory. It shows how, with UML, simple models of business processes and specification models can be created and read with little effort.

This book is a mini tutorial with plenty of code examples and strategies to give you many options when building your own applications.This book is meant for readers who are familiar with C/C++ programming and want to write simple programs with Kinect. The standard template library can also be used as it is simple enough to understand.

A friendly, tutorial style book, which will help you learn your way through creating a live storefront with nopCommerce in a step-by-step manner.Getting Started with nopCommerce is for anyone who wants to sell products online using nopCommerce. If you are a non-technical person and are discouraged by the complexity of this powerful e-commerce application, then this book is for you.

If you are a professional, student, or educator who wants to learn to use IPython Notebook as a tool for technical and scientific computing, visualization, and data analysis, this is the book for you. This book will prove valuable for anyone that needs to do computations in an agile environment.