This book gives you exactly what you need, exactly when you need it. Using easy-to-follow practical examples, this guide takes you from simple presentations to complete websites in no time. If you want to engage your audience on a level not previously possible on software such as PowerPoint or Prezi, then this book is for you. With basic knowledge of HTML, CSS, and JavaScript you can start making presentations that truly Impress.

This is a stepby step, tutorialbased book which will enable web developers to explore the functionalities of Jade and learn how to use it to write certain functions and processes for web development. This book is for web developers with at least a basic understanding of HTML and JavaScript. It will enable you to write an easier form of language that then compiles into HTML.

If you have a basic understanding of the C++ programming language and want to create videogames for the Android platform, then this technology and book is ideal for you.

If you are a developer with BeagleBone experience and want to learn how to use it to set up a network and file server, then this book is ideal for you. To make the most of this book, you should be comfortable with the Linux operating system and know how to install software from the Internet, but you do not have to be a network guru.

Learn how some Go-specific language features help to simplify building web scrapers along with common pitfalls and best practices regarding web scraping. Key Features * Use Go libraries like Goquery and Colly to scrape the web * Common pitfalls and best practices to effectively scrape and crawl * Learn how to scrape using the Go concurrency model Book Description Web scraping is the process of extracting information from the web using various tools that perform scraping and crawling. Go is emerging as the language of choice for scraping using a variety of libraries. This book will quickly explain to you, how to scrape data data from various websites using Go libraries such as Colly and Goquery. The book starts with an introduction to the use cases of building a web scraper and the main features of the Go programming language, along with setting up a Go environment. It then moves on to HTTP requests and responses and talks about how Go handles them. You will also learn about a number of basic web scraping etiquettes. You will be taught how to navigate through a website, using a breadth-first and then a depth-first search, as well as find and follow links. You will get to know about the ways to track history in order to avoid loops and to protect your web scraper using proxies. Finally the book will cover the Go concurrency model, and how to run scrapers in parallel, along with large-scale distributed web scraping. What you will learn * Implement Cache-Control to avoid unnecessary network calls * Coordinate concurrent scrapers * Design a custom, larger-scale scraping system * Scrape basic HTML pages with Colly and JavaScript pages with chromedp * Discover how to search using the "strings" and "regexp" packages * Set up a Go development environment * Retrieve information from an HTML document * Protect your web scraper from being blocked by using proxies * Control web browsers to scrape JavaScript sites Who this book is for Data scientists, and web developers with a basic knowledge of Golang wanting to collect web data and analyze them for effective reporting and visualization.

Solve real-world statistical problems using the most popular R packages and techniques Key Features * Learn how to apply statistical methods to your everyday research with handy recipes * Foster your analytical skills and interpret research across industries and business verticals * Perform t-tests, chi-squared tests, and regression analysis using modern statistical techniques Book Description R is a popular programming language for developing statistical software. This book will be a useful guide to solving common and not-so-common challenges in statistics. With this book, you'll be equipped to confidently perform essential statistical procedures across your organization with the help of cutting-edge statistical tools. You'll start by implementing data modeling, data analysis, and machine learning to solve real-world problems. You'll then understand how to work with nonparametric methods, mixed effects models, and hidden Markov models. This book contains recipes that will guide you in performing univariate and multivariate hypothesis tests, several regression techniques, and using robust techniques to minimize the impact of outliers in data.You'll also learn how to use the caret package for performing machine learning in R. Furthermore, this book will help you understand how to interpret charts and plots to get insights for better decision making. By the end of this book, you will be able to apply your skills to statistical computations using R 3.5. You will also become well-versed with a wide array of statistical techniques in R that are extensively used in the data science industry. What you will learn * Become well versed with recipes that will help you interpret plots with R * Formulate advanced statistical models in R to understand its concepts * Perform Bayesian regression to predict models and input missing data * Use time series analysis for modelling and forecasting temporal data * Implement a range of regression techniques for efficient data modelling * Get to grips with robust statistics and hidden Markov models * Explore ANOVA (Analysis of Variance) and perform hypothesis testing Who this book is for If you are a quantitative researcher, statistician, data analyst, or data scientist looking to tackle various challenges in statistics, this book is what you need! Proficiency in R programming and basic knowledge of linear algebra is necessary to follow along the recipes covered in this book.

Learn how to use Unreal Engine 4 by building 3D and multiplayer games using Blueprints Key Features * Learn the fundamentals of Unreal Engine such as project templates, Blueprints, and C++ * Learn to design games; use UMG to create menus and HUDs, and replication to create multiplayer games * Build dynamic game elements using Animation Blueprints and Behavior Trees Book Description Unreal Engine is a popular game engine for developers to build high-end 2D and 3D games. This book is a practical guide, starting off by quickly introducing you to the Unreal Engine 4 (UE4) ecosystem. You will learn how to create Blueprints and C++ code to define your game's functionality. You will be familiarized with the core systems of UE4 such as UMG, Animation Blueprints, and Behavior Trees. You will also learn how to use replication to create multiplayer games. By the end of this book, you will have a broad, solid knowledge base to expand upon on your journey with UE4. What you will learn * Use project templates to give your game a head start * Create custom Blueprints and C++ classes and extend from Epic's base classes * Use UMG to create menus and HUDs for your game * Create more dynamic characters using Animation Blueprints * Learn how to create complex AI with Behavior Trees * Use replication to create multiplayer games * Optimize, test, and deploy a UE4 project Who this book is for Readers who already have some game development experience and Unity users who would like to try UE4 will all benefit from this book. Knowledge of basic Object-Oriented Programming topics such as variables, functions, and classes is assumed.

Leverage Docker to unlock efficient and rapid container deployments to improve your development workflow Key Features * Reconfigure Docker hosts to create a logging system with the ElasticSearch-Logstash-Kibana (ELK) stack * Tackle the challenges of large-scale container deployment with this fast-paced guide * Benchmark the performance of your Docker containers using Apache JMeter Book Description Docker is an enterprise-grade container platform that allows you to build and deploy your apps. Its portable format lets you run your code right from your desktop workstations to popular cloud computing providers. This comprehensive guide will improve your Docker work?ows and ensure your application's production environment runs smoothly. This book starts with a refresher on setting up and running Docker and details the basic setup for creating a Docker Swarm cluster. You will then learn how to automate this cluster by using Chef Server and Cookbook. After that, you will run the Docker monitoring system with Prometheus and Grafana, and deploy the ELK stack. You will also learn some tips for optimizing Docker images. After deploying containers with the help of Jenkins, you will then move on to a tutorial on using Apache JMeter to analyze your application's performance. You will learn how to use Docker Swarm and NGINX to load-balance your application and how common debugging tools in Linux can be used to troubleshoot Docker containers. By the end of this book, you will be able to integrate all the optimizations that you have learned and put everything into practice in your applications. What you will learn * Automate provisioning and setting up nodes in a Docker Swarm cluster * Configure a monitoring system with Prometheus and Grafana * Use Apache JMeter to create workloads for benchmarking the performance of Docker containers * Understand how to load-balance an application with Docker Swarm and Nginx * Deploy strace, tcdump, blktrace, and other Linux debugging tools to troubleshoot containers * Integrate Docker optimizations for DevOps, Site Reliability Engineering, CI, and CD Who this book is for If you are a software developer with a good understanding of managing Docker services and the Linux file system and are looking for ways to optimize working with Docker containers, then this is the book for you. Developers fascinated with containers and workflow automation with benefit from this book.

Teach your machine to think for itself! Key Features * Delve into supervised learning and grasp how a machine learns from data * Implement popular machine learning algorithms from scratch, developing a deep understanding along the way * Explore some of the most popular scientific and mathematical libraries in the Python language Book Description Supervised machine learning is used in a wide range of sectors (such as finance, online advertising, and analytics) because it allows you to train your system to make pricing predictions, campaign adjustments, customer recommendations, and much more while the system self-adjusts and makes decisions on its own. As a result, it's crucial to know how a machine “learns” under the hood. This book will guide you through the implementation and nuances of many popular supervised machine learning algorithms while facilitating a deep understanding along the way. You’ll embark on this journey with a quick overview and see how supervised machine learning differs from unsupervised learning. Next, we explore parametric models such as linear and logistic regression, non-parametric methods such as decision trees, and various clustering techniques to facilitate decision-making and predictions. As we proceed, you'll work hands-on with recommender systems, which are widely used by online companies to increase user interaction and enrich shopping potential. Finally, you’ll wrap up with a brief foray into neural networks and transfer learning. By the end of this book, you’ll be equipped with hands-on techniques and will have gained the practical know-how you need to quickly and powerfully apply algorithms to new problems. What you will learn * Crack how a machine learns a concept and generalize its understanding to new data * Uncover the fundamental differences between parametric and non-parametric models * Implement and grok several well-known supervised learning algorithms from scratch * Work with models in domains such as ecommerce and marketing * Expand your expertise and use various algorithms such as regression, decision trees, and clustering * Build your own models capable of making predictions * Delve into the most popular approaches in deep learning such as transfer learning and neural networks Who this book is for This book is for aspiring machine learning developers who want to get started with supervised learning. Intermediate knowledge of Python programming—and some fundamental knowledge of supervised learning—are expected.

Learn how to write automated tests for Dynamics 365 Business Central and see how to implement it in your daily work Key Features * Leverage automated testing to advance over traditional manual testing methods * Write, design, and implement automated tests * Explore various testing frameworks and tools compatible with Microsoft Dynamics 365 Business Central Book Description Dynamics 365 Business Central is the new cloud-based SaaS ERP proposition from Microsoft. It’s not as simple as it used to be way back when it was called Navigator, Navision Financials, or Microsoft Business Solutions-Navision. Our development practices are becoming more formal, and with this, the call for test automation is pressing on us. This book will teach you to leverage testing tools available with Dynamics 365 Business Central to perform automated testing. We’ll begin with a quick introduction to automated testing, followed by an overview of test automation in Dynamics 365 Business Central. Then you’ll learn to design and build automated tests and we’ll go through some efficient methods to get from requirements to application and testing code. Lastly, you’ll learn to incorporate your own and Microsoft tests into your daily development practice. By the end of the book, you’ll be able to write your own automated tests for Dynamics 365 Business Central. What you will learn * Understand what automated tests are, and when and why to use them * Explore the five pillars of the Testability Framework of Business Central * Design and write automated tests for Business Central * Make use of standard automated tests and their helper libraries * Integrate automated tests into your development practice Who this book is for This book is for consultants, testers, developers, and development managers working with Microsoft Dynamics NAV and Business Central. Being a book on automated testing techniques, it also caters to both functional and technical development teams.

Build and train scalable neural network models on various platforms by leveraging the power of Caffe2 Key Features * Migrate models trained with other deep learning frameworks on Caffe2 * Integrate Caffe2 with Android or iOS and implement deep learning models for mobile devices * Leverage the distributed capabilities of Caffe2 to build models that scale easily Book Description Caffe2 is a popular deep learning library used for fast and scalable training and inference of deep learning models on various platforms. This book introduces you to the Caffe2 framework and shows how you can leverage its power to build, train, and deploy efficient neural network models at scale. It will cover the topics of installing Caffe2, composing networks using its operators, training models, and deploying models to different architectures. It will also show how to import models from Caffe and from other frameworks using the ONNX interchange format. It covers the topic of deep learning accelerators such as CPU and GPU and shows how to deploy Caffe2 models for inference on accelerators using inference engines. Caffe2 is built for deployment to a diverse set of hardware, using containers on the cloud and resource constrained hardware such as Raspberry Pi, which will be demonstrated. By the end of this book, you will be able to not only compose and train popular neural network models with Caffe2, but also be able to deploy them on accelerators, to the cloud and on resource constrained platforms such as mobile and embedded hardware. What you will learn * Build and install Caffe2 * Compose neural networks * Train neural network on CPU or GPU * Import a neural network from Caffe * Import deep learning models from other frameworks * Deploy models on CPU or GPU accelerators using inference engines * Deploy models at the edge and in the cloud Who this book is for Data scientists and machine learning engineers who wish to create fast and scalable deep learning models in Caffe2 will find this book to be very useful. Some understanding of the basic machine learning concepts and prior exposure to programming languages like C++ and Python will be useful.

This quick start guide will bring the readers to a basic level of understanding when it comes to the Machine Learning (ML) development lifecycle, will introduce Go ML libraries and then will exemplify common ML methods such as Classification, Regression, and Clustering Key Features * Your handy guide to building machine learning workflows in Go for real-world scenarios * Build predictive models using the popular supervised and unsupervised machine learning techniques * Learn all about deployment strategies and take your ML application from prototype to production ready Book Description 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. What you will learn * Understand the types of problem that machine learning solves, and the various approaches * Import, pre-process, and explore data with Go to make it ready for machine learning algorithms * Visualize data with gonum/plot and Gophernotes * Diagnose common machine learning problems, such as overfitting and underfitting * Implement supervised and unsupervised learning algorithms using Go libraries * Build a simple web service around a model and use it to make predictions Who this book is for This book is for developers and data scientists with at least beginner-level knowledge of Go, and a vague idea of what types of problem Machine Learning aims to tackle. No advanced knowledge of Go (and no theoretical understanding of the math that underpins Machine Learning) is required.

Get to grips with a new technology, understand what it is and what it can do for you, and then get to work with the most important features and tasks. Instant Highcharts Starter has a step-by-step approach to help you understand the core concepts of different types of Highcharts and create your own customized charts.Instant Highcharts Starter is for web developers who are new to the Highcharts library and looking to create their own charts in their webpages. You should have some experience with the JavaScript library. You should know how to develop a server-side language such as PHP to create dynamic Highcharts.

This book is divided into projects that are explained in a step-by-step format, with practical instructions that are easy to follow. If you want to build your own home automation systems wirelessly using the Arduino platform, this is the book for you. You will need to have some basic experience in Arduino and general programming languages, such as C and C++ to understand the projects in this book.

Real-world examples of cross-browser, mobile, and data-driven testing with all the latest features of Selenium WebDriver 3 Key Features *Unlock the full potential of Selenium to test your web applications *Use Selenium Grid for faster, parallel running, and cross-browser testing *Test iOS and Android Apps with Appium Book Description Selenium WebDriver is an open source automation tool implemented through a browser-specific driver, which sends commands to a browser and retrieves results. The latest version of Selenium 3 brings with it a lot of new features that change the way you use and setup Selenium WebDriver. This book covers all those features along with the source code, including a demo website that allows you to work with an HMTL5 application and other examples throughout the book. Selenium WebDriver 3 Practical Guide will walk you through the various APIs of Selenium WebDriver, which are used in automation tests, followed by a discussion of the various WebDriver implementations available. You will learn to strategize and handle rich web UI using advanced WebDriver API along with real-time challenges faced in WebDriver and solutions to handle them. You will discover different types and domains of testing such as cross-browser testing, load testing, and mobile testing with Selenium. Finally, you will also be introduced to data-driven testing using TestNG to create your own automation framework. By the end of this book, you will be able to select any web application and automate it the way you want. What you will learn *Understand what Selenium 3 is and how is has been improved than its predecessor *Use different mobile and desktop browser platforms with Selenium 3 *Perform advanced actions, such as drag-and-drop and action builders on web page *Learn to use Java 8 API and Selenium 3 together *Explore remote WebDriver and discover how to use it *Perform cross browser and distributed testing with Selenium Grid *Use Actions API for performing various keyboard and mouse actions Who this book is for Selenium WebDriver 3 Practical Guide is for software quality assurance/testing professionals, software project managers, or software developers interested in using Selenium for testing their applications. Prior programming experience in Java is necessary.

This tutorial contains allimportant information about how to use your Raspberry Pi to develop any application you like. It is broken down into several actionpacked projects, each containing easytofollow steps, just to show you how easy and fun computer programming can be! If you are someone with a big imagination and would like to dive straight into the realm of technology and computers, then this is the book for you. With only a Raspberry Pi and no prior experience required, you will be shown how to translate your ideas into computer programs, creating any game, tool, or animation you can dream of.

Get to grips with a new technology, understand what it is and what it can do for you, and then get to work with the most important features and tasks. MongoDB Starter is a fast and practical guide designed to help you start developing high-performance and scalable applications using MongoDB.MongoDB Starter is ideal for developers who are new to MongoDB and who need a no-nonsense guide on how to start working with it. No knowledge of MongoDB is required to follow this book, but some knowledge of C++ would be helpful.

Master the fundamentals of programming in Swift 4 About This Book ? Covers theory and practice in equal parts ? Teaches you how to correctly structure and architect software using Swift ? Uses real-world examples to connect the theory to a professional setting ? Imparts expertise in the core Swift standard library Who This Book Is For If you are seeking fundamental Swift programming skills, in preparation for learning to develop native applications for iOS or macOS, this book is the best for you. You don’t need to have any prior Swift knowledge; however, object-oriented programming experience is desired. What You Will Learn ? Explore the fundamental Swift programming concepts, language structure, and the Swift programming syntax ? Learn how Swift compares to other computer languages and how to transform your thinking to leverage new concepts such as optionals and protocols ? Master how to use key language elements, such as strings and collections ? Grasp how Swift supports modern application development using advanced features, such as built-in Unicode support and higher-order functions. In Detail Take your first foray into programming for Apple devices with Swift. Swift is fundamentally different from Objective-C, as it is a protocol-oriented language. While you can still write normal object-oriented code in Swift, it requires a new way of thinking to take advantage of its powerful features and a solid understanding of the basics to become productive. This course helps you develop client-side and server-side applications, as well as web services using Swift. We'll begin with exploring the fundamental Swift programming concepts, language structure, and the Swift programming syntax. Then, we'll learn to create original custom operators with Swift operators, branching, and loops. Moving on, we'll learn how to run application codes and compile errors. Having made progress with it, we'll see how Swift compares to other computer languages and how to transform your thinking. Then, master the usage of key language elements, such as strings and collections. Finally, grasp how Swift supports modern application development using advanced features, such as built-in Unicode support and higher-order functions. This is an introductory course to the Swift programming language with Xcode.After completing this course, students will be well-prepared to begin developing native end-user applications for iOS or macOS, or to develop server-side (back-end) application and web services using Swift on Linux. Style and approach This is an introductory course to the Swift programming language with Xcode. The course does not expect you to have any previous Swift knowledge or experience. The course covers ample amount of exercises so that students learn the basics hands-on.

Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. Instant Microsoft SQL Server Analysis Services 2012 Cube Security is a practical, hands-on guide that provides a number of clear, step-by-step exercises for getting started with cube security.This book is aimed at Database Administrators, Data Architects, and Systems Administrators who are managing the SQL Server data platform. It is also beneficial for analysis services developers who already have some experience with the technology, but who want to go into more detail on advanced topics and learn best practices for cube design.

Build modern, fast, and progressive web applications using modern features of PHP 7 and TypeScript Key Features *Explore the latest features of Angular and Laravel to build applications that are powerful, consistent, and maintainable *Develop modern user interfaces with a reusable component-based architecture using Angular 6 and Bootstrap 4 *Learn how to build secure backend APIs with Laravel Book Description Angular, considered as one of the most popular and powerful frontend frameworks, has undergone a major overhaul to embrace emerging web technologies so that developers can build cutting-edge web applications. This book gives you practical knowledge of building modern full-stack web apps from scratch using Angular with a Laravel Restful back end. The book begins with a thorough introduction to Laravel and Angular and its core concepts like custom errors messages, components, routers, and Angular-cli, with each concept being explained first, and then put into practice in the case-study project. With the basics covered, you will learn how sophisticated UI features can be added using NgBootstrao and a component-based architecture. You will learn to extend and customize variables from Bootstrap CSS framework. You will learn how to create secure web application with Angular and Laravel using token based authentication. Finally, you will learn all about progressive web applications and build and deploy a complete fullstack application using Docker and Docker-compose. By the end of this book, you'll gain a solid understanding of Angular 6 and how it interacts with a Laravel 5.x backend What you will learn *Explore the core features of Angular 6 to create sophisticated user interfaces *Use Laravel 5 to its full extent to create a versatile backend layer based on RESTful APIs *Configure a web application in order to accept user-defined data and persist it into the database using server-side APIs *Build an off-line-first application using service-worker and manifest file *Deal with token based authentication on single page application (SPA). *Secure your application against threats and vulnerabilities in a time efficient way *Deploy using Docker and Docker-compose Who this book is for This book targets developers who are new to Angular, Laravel, or both, and are seeking a practical, best-practice approach to development with these technologies. They must have some knowledge of HTML, CSS and JavaScript. Familiarity of PHP is assumed to get the most from this book.

Use PySpark to easily crush messy data at-scale and discover proven techniques to create testable, immutable, and easily parallelizable Spark jobs Key Features * Work with large amounts of agile data using distributed datasets and in-memory caching * Source data from all popular data hosting platforms, such as HDFS, Hive, JSON, and S3 * Employ the easy-to-use PySpark API to deploy big data Analytics for production Book Description Apache Spark is an open source parallel-processing framework that has been around for quite some time now. One of the many uses of Apache Spark is for data analytics applications across clustered computers. In this book, you will not only learn how to use Spark and the Python API to create high-performance analytics with big data, but also discover techniques for testing, immunizing, and parallelizing Spark jobs. You will learn how to source data from all popular data hosting platforms, including HDFS, Hive, JSON, and S3, and deal with large datasets with PySpark to gain practical big data experience. This book will help you work on prototypes on local machines and subsequently go on to handle messy data in production and at scale. This book covers installing and setting up PySpark, RDD operations, big data cleaning and wrangling, and aggregating and summarizing data into useful reports. You will also learn how to implement some practical and proven techniques to improve certain aspects of programming and administration in Apache Spark. By the end of the book, you will be able to build big data analytical solutions using the various PySpark offerings and also optimize them effectively. What you will learn * Get practical big data experience while working on messy datasets * Analyze patterns with Spark SQL to improve your business intelligence * Use PySpark's interactive shell to speed up development time * Create highly concurrent Spark programs by leveraging immutability * Discover ways to avoid the most expensive operation in the Spark API: the shuffle operation * Re-design your jobs to use reduceByKey instead of groupBy * Create robust processing pipelines by testing Apache Spark jobs Who this book is for This book is for developers, data scientists, business analysts, or anyone who needs to reliably analyze large amounts of large-scale, real-world data. Whether you're tasked with creating your company's business intelligence function or creating great data platforms for your machine learning models, or are looking to use code to magnify the impact of your business, this book is for you.