Build, process and analyze large-scale graph data effectively with Spark About This Book Find solutions for every stage of data processing from loading and transforming graph data to Improve the scalability of your graphs with a variety of real-world applications with complete Scala code. A concise guide to processing large-scale networks with Apache Spark. Who This Book Is For This book is for data scientists and big data developers who want to learn the processing and analyzing graph datasets at scale. Basic programming experience with Scala is assumed. Basic knowledge of Spark is assumed. What You Will Learn Write, build and deploy Spark applications with the Scala Build Tool. Build and analyze large-scale network datasets Analyze and transform graphs using RDD and graph-specific operations Implement new custom graph operations tailored to specific needs. Develop iterative and efficient graph algorithms using message aggregation and Pregel abstraction Extract subgraphs and use it to discover common clusters Analyze graph data and solve various data science problems using real-world datasets. In Detail Apache Spark is the next standard of open-source cluster-computing engine for processing big data. Many practical computing problems concern large graphs, like the Web graph and various social networks. The scale of these graphs - in some cases billions of vertices, trillions of edges - poses challenges to their efficient processing. Apache Spark GraphX API combines the advantages of both data-parallel and graph-parallel systems by efficiently expressing graph computation within the Spark data-parallel framework. This book will teach the user to do graphical programming in Apache Spark, apart from an explanation of the entire process of graphical data analysis. You will journey through the creation of graphs, its uses, its exploration and analysis and finally will also cover the conversion of graph elements into graph structures. This book begins with an introduction of the Spark system, its libraries and the Scala Build Tool. Using a hands-on approach, this book will quickly teach you how to install and leverage Spark interactively on the command line and in a standalone Scala program. Then, it presents all the methods for building Spark graphs using illustrative network datasets. Next, it will walk you through the process of exploring, visualizing and analyzing different network characteristics. This book will also teach you how to transform raw datasets into a usable form. In addition, you will learn powerful operations that can be used to transform graph elements and graph structures. Furthermore, this book also teaches how to create custom graph operations that are tailored for specific needs with efficiency in mind. The later chapters of this book cover more advanced topics such as clustering graphs, implementing graph-parallel iterative algorithms and learning methods from graph data. Style and approach A step-by-step guide that will walk you through the key ideas and techniques for processing big graph data at scale, with practical examples that will ensure an overall understanding of the concepts of Spark.

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world’s leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you’ll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

Extract valuable data from your social media sites and make better business decisions using R About This Book Explore the social media APIs in R to capture data and tame it Employ the machine learning capabilities of R to gain optimal business value A hands-on guide with real-world examples to help you take advantage of the vast opportunities that come with social media data Who This Book Is For If you have basic knowledge of R in terms of its libraries and are aware of different machine learning techniques, this book is for you. Those with experience in data analysis who are interested in mining social media data will find this book useful. What You Will Learn Access APIs of popular social media sites and extract data Perform sentiment analysis and identify trending topics Measure CTR performance for social media campaigns Implement exploratory data analysis and correlation analysis Build a logistic regression model to detect spam messages Construct clusters of pictures using the K-means algorithm and identify popular personalities and destinations Develop recommendation systems using Collaborative Filtering and the Apriori algorithm In Detail With an increase in the number of users on the web, the content generated has increased substantially, bringing in the need to gain insights into the untapped gold mine that is social media data. For computational statistics, R has an advantage over other languages in providing readily-available data extraction and transformation packages, making it easier to carry out your ETL tasks. Along with this, its data visualization packages help users get a better understanding of the underlying data distributions while its range of "standard" statistical packages simplify analysis of the data. This book will teach you how powerful business cases are solved by applying machine learning techniques on social media data. You will learn about important and recent developments in the field of social media, along with a few advanced topics such as Open Authorization (OAuth). Through practical examples, you will access data from R using APIs of various social media sites such as Twitter, Facebook, Instagram, GitHub, Foursquare, LinkedIn, Blogger, and other networks. We will provide you with detailed explanations on the implementation of various use cases using R programming. With this handy guide, you will be ready to embark on your journey as an independent social media analyst. Style and approach This easy-to-follow guide is packed with hands-on, step-by-step examples that will enable you to convert your real-world social media data into useful, practical information.

Extend the capabilities of AngularJS and build dynamic web applications by creating customized directives with this selection of more than 30 recipes About This Book Learn how to extend HTML templates in new ways to build even better web applications with exceptional interface components Build reusable directives for large-scale AngularJS applications Create even sophisticated and impressive modern web apps with ease Who This Book Is For This book is for developers with AngularJS experience who want to extend their knowledge to create or customize directives in any type of AngularJS application. Some experience of modern tools such as Yeoman and Bower would be helpful, but is not a requirement. What You Will Learn Build and customize external HTML templates, and create simple, effective directives for common interface components Learn how to use Controller function and any Bootstrap UI directives to manipulate the DOM and how to transform any UI library into AngularJS directives Construct an AngularJS application to use shared components and validate your HTML5 Discover how to use jQuery events and manipulate the DOM using jQuery UI inside AngularJS applications Create custom directives for ongoing projects using Yeoman generators, and find out how to implement standalone directives Build reusable directives for Large AngularJS applications and extend directives to use dynamic templates Write unit test for directives using the Karma runner and Jasmine’s behavior-driven development framework In Detail AngularJS directives are at the center of what makes it such an exciting – and important - web development framework. With directives, you can take greater control over HTML elements on your web pages – they ‘direct’ Angular’s HTML compiler to behave in the way you want it to. It makes building modern web applications a much more expressive experience, and allows you to focus more closely on improving the way that user interaction impacts the DOM and the way your app manages data. If you’re already using Angular, you probably recognize the power of directives to transform the way you understand and build your projects – but customizing and creating your own directives to harness AngularJS to its full potential can be more challenging. This cookbook shows you how to do just that – it’s a valuable resource that demonstrates how to use directives at every stage in the workflow. Packed with an extensive range of solutions and tips that AngularJS developers shouldn’t do without, you’ll find out how to make the most of directives. You’ll find recipes demonstrating how to build a number of different user interface components with directives, so you can take complete control over how users interact with your application. You’ll also learn how directives can simplify the way you work by creating reusable directives – by customizing them with Yeoman you can be confident that you’re application has the robust architecture that forms the bedrock of the best user experiences. You’ll also find recipes that will help you learn how to unit test directives, so you can be confident in the reliability and performance of your application. Whether you’re looking for guidance to dive deeper into AngularJS directives, or you want a reliable resource, relevant to today’s web development challenges, AngularJS Directives Cookbook delivers everything you need in an easily accessible way. Style and approach This book easy-to-follow guide is packed with hands-on recipes to help you build modular AngularJS applications with custom directives. It presents tips on using the best tools and various ways to use these tools for front-end development.

The book is intended for those who want to know more about network penetration tests and have no prior experience, as well as for those who are experienced in network systems and are interested in discovering more about this topic.

If you are a programmer with an interest in building advanced robotics projects using inexpensive hardware and open source software, then this book is for you. Some experience with computer programming and implementing simple mechanical systems is required.

This book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and pointers to learning resources.

This book is for testers looking for quick access to powerful, modern tools and customizable *s to kick-start the creation of their own Python web penetration testing toolbox.

It is assumed that you will already have a server up and running, you have a good working knowledge of CentOS, and you are comfortable with the concept of working with those services used by your server.

This book is perfect for R programmers who are interested in learning to use ggplot2 for data visualization, from the basics up to using more advanced applications, such as faceting and grouping. Since this book will not cover the basics of R commands and objects, you should have a basic understanding of the R language.

This book will help beginners to create stylish and professional looking dashboards in no time. It is also intended for BI developers who want to use SAP BO to facilitate BI in their organizations. No prior knowledge is required, however, you must have a basic knowledge of MS Excel and some analytical skills to build expressive business charts.

The book is best suited for existing Android or Java programmers who want to adapt their skills to make exciting Android games. The book is also for determined readers who might have no Android, game programming or even Java experience, but a reasonable understanding of object oriented programming knowledge is assumed.

This book is ideal for system developers with knowledge and experience of embedded systems. Knowledge of BeagleBone Black is assumed, while no knowledge of Yocto Project build system is necessary.

This book is intended for IT administrators who want to use Citrixas a desktop virtualization solution or for IT architects who want to learn how to design and implement highly available and scalable XenDesktopenvironments. It is assumed that you have intermediate-level knowledge of virtualization concepts, Windows desktop operating systems, and Windows Server technologies. Citrix?, Citrix Systems?, XenApp?, XenDesktop?, and CloudPortalare trademarks of CitrixSystems?, Inc. and/or one or more of its subsidiaries, and may be registered in the United States Patent and Trademark Office and in other countries.

This book is intended for middleware system administrators and Java developers, actually good Java developers, who care about architecture design and implementation. Whether you are new to WildFly, come from a previous version, such as JBoss AS 5, 6, and 7, or are an expert in it, you will be able to master both the basic and advanced features of WildFly. By the way, most of the core components of WildFly are totally new, such as its administration tool, that is, the CLI; its operational modes, which are, the standalone and domain modes; and its web server provided by Undertow, you can benefit from this book even if you have no experience in JBoss and WildFly at all.

FreeSWITCH 1.6 Cookbook is written for anyone who wants to learn more about using FreeSWITCH in production. The information is presented in such a way that you can get up and running quickly. The cookbook approach eschews much of the foundational concepts, and instead focuses on discrete examples that illustrate specific features. If you need to implement a particular feature as quickly as possible, then this book is for you.

This book is for all programmers and game enthusiasts who want to stop dreaming about creating a game, and actually create one from scratch. The reader should know the basics of programming and using the Lua language. Knowledge of the C/C++ programming language is not necessary, but it's strongly recommended in order to write custom Lua modules extending game engine capabilities or to rewrite parts of the Lua code into a more efficient form. Algebra and matrix operations are required in order to understand advanced topics in Chapter 4, Graphics – Legacy Method with OpenGL 1.x-2.1 and Chapter 5, Graphics – Modern Method with OpenGL 3.0+. Sample demonstrations are coupled with binary libraries for Windows and Linux operating systems for convenience.

If you are a data analyst with basic knowledge of Big Data analysis but no knowledge of Splunk, then this book will help you get started with Splunk. The book assumes that you have access to a copy of Splunk, ideally not in production, and many examples also assume you have administrator rights.

If you are network administrator or a security analyst with an interest in using Wireshark for security analysis, then this is the book for you. Basic familiarity with common network and application services terms and technologies is assumed.

This book is for messaging professionals who want to build real-world *s with Windows PowerShell 5 and the Exchange Management Shell. If you are a network or systems administrator responsible for managing and maintaining Exchange Server 2013, you will find this highly useful.

If you are an Android developer who wants to learn how to build applications for the Android Wear platform, then this is the book for you. This book only requires a basic knowledge of Android programming. Familiarity with development IDEs such as Android Studio, IntelliJ IDEA, or Eclipse will be helpful.