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.

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.

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.

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.

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.

A short and straight to the point guide that explains the implementation of Regular Expressions in Python. This book is aimed at Python developers who want to learn how to leverage Regular Expressions in Python. Basic knowledge of Python is required for a better understanding.

This book is for kids who wish to develop games and applications using the Raspberry Pi. No prior experience in programming is necessary; you need only a Raspberry Pi and the required peripherals.

If you are a software developer with little or no experience of versioning systems, or are familiar with other centralized versioning systems, then this book is for you. If you have some experience working with command lines or using Linux admin or just using Unix and want to know more about Git, then this book is ideal for you.

If you are an Ext JS or Sencha Touch developer, designer, or architect who wants to build enterprise-scale data visualization capabilities using Sencha, then this book is ideal for you. You should have a knowledge of HTML, JavaScript, CSS, and Sencha Ext JS or Sencha Touch fundamentals, in particular. Some familiarity with SVG and HTML5 Canvas would be preferred, but not required.

Filled with practical, stepbystep instructions and clear explanations for the most important and useful tasks. A concise guide full of stepbystep recipes to teach you how to create CasperJS tests for your web development projects. This book will be extremely useful for web developers who are new to testing or who want to move from another testing solution to CasperJS. It is assumed that you are familiar with web development and have a good knowledge of JavaScript.

If you want to create your own game, but don't know where to start, this is the book for you. Whether you've used GameSalad before, or have prior game development experience or not you are sure to learn! Imaging software experience, such as Photoshop, is good to have, but art and assets are provided in the book's resources.

If you are someone who loves to play games and are interested in learning more about the capabilities of your Raspberry Pi, this book is for you. Basic knowledge of Raspberry Pi programming is expected.

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. This book is for IT professionals who have no previous experience with Netcat but need to understand it quickly and easily.

Whether you are a hobbyist or a professional, this book will get you fully equipped to resolve the most commonly occurring media-related challenges. If you want to expand your horizons beyond lighting an LED and push the limits of your board, this is just the book for you. Working knowledge of BeagleBone is assumed.

A short book with a lot of hands-on examples to help you learn in a practical way.This book is great for users, developers, and consultants who know the basic functions and processes of a GIS but want to know how to use QGIS to achieve the results they are used to a full-fledged GIS.

Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. Get the job done and learn as you go. A practical guide comprising of easy-to-follow recipes which provide concise and clear steps to help you enter the world of RubyMine.Instant RubyMine is ideal for you, if you are new to RubyMine or well acquainted with the technology. All you need is basic knowledge of writing in Ruby or Ruby on Rails.

This book is for users experienced with game development who now want to learn how to develop games in GameMaker: Studio in a fast-paced way.