If you want to learn to write your own *s for the Nmap Scripting Engine, this is the book for you. It is perfect for network administrators, information security professionals, and even Internet enthusiasts who are familiar with Nmap.

This book is intended for anybody who wants to learn how they can utilize the capabilities of the Banana Pi to its full potential. It's full of step-by-step guides and detailed de*ions for the whole range of possibilities in a language that is appropriate for computer enthusiasts and experts alike. It would be helpful to have a basic knowledge of Unix-like operating systems or programming, but no prior experience is required as every concept is explained in the appropriate sections.

If you're a frontend developer with knowledge of native JavaScript or jQuery, along with frontend frameworks such as Angular.js and Backbone.js, and your aim is to build maintainable and scalable web user interfaces, then this book is ideal for you.

This book is aimed at system administrators and technical architects moving from a virtualized environment to cloud environments; who are familiar with cloud computing platforms. Knowledge of virtualization and managing Linux environments is expected. Prior knowledge or experience of OpenStack is not required, although beneficial.

If you are a beginner or an intermediate GIS user, this book is for you. It is ideal for practitioners, data analysts, and application developers who have very little or no familiarity with geospatial data and software.

This book is for developers and data architects who have some exposure to databases. It is assumed that you understand the basic concepts of tables and common database objects, including privileges and security.

If you are a professional or enthusiast who has a basic understanding of graphs or has basic knowledge of Neo4j operations, this is the book for you. Although it is targeted at an advanced user base, this book can be used by beginners as it touches upon the basics. So, if you are passionate about taming complex data with the help of graphs and building high performance applications, you will be able to get valuable insights from this book.

This book is for anyone who wants to have a go at creating commercially successfully games for Android and iOS. You don’t need game development or programming experience.

This book is for coding students and Java programmers of all levels interested in building engaging, interactive applications with Greenfoot. Familiarity with the very basics of Greenfoot is assumed.

If you want to build programming and electronics projects that interact with the environment, this book will offer you dozens of recipes to guide you through all the major applications of the Arduino platform. It is intended for programming or electronics enthusiasts who want to combine the best of both worlds to build interactive projects.

If you are a web developer who wants to create well designed WebRTC applications for your users, this is the book for you. Even if you are early in your web development career, this book aims to provide a complete understanding of the WebRTC API. It is assumed that you have previous exposure to web development using HTML5 and JavaScript technologies.

If you are an application developer with some experience in software testing and want to learn more about testing frameworks, then this technology and book is for you. Mockito for Spring will be perfect as your next step towards becoming a competent software tester with Spring and Mockito.

This book is intended for software developers who want to use parallel programming techniques to write powerful and efficient code. After reading this book, you will be able to master the basics and the advanced features of parallel computing. The Python programming language is easy to use and allows nonexperts to deal with and easily understand the topics exposed in this book.

Each chapter follows the creation of a social networking application with step-by-step instructions. This means that you will have easily created a complete, working application by the end of the book. This book is for beginner and intermediate PHP developers interested in using CouchDB development in their projects. Advanced PHP developers will appreciate the familiarity of the PHP architecture and can easily learn how to incorporate CouchDB into their existing development experiences.

This book is a step-by-step tutorial that includes complete source code for all of the examples covered. Every chapter builds on top of the previous one thereby giving the reader an immediate feeling of progression. Each block of code is explained, and 3D web development concepts are diagrammed and covered in detail. This book is written for JavaScript developers who are interested in 3D web development. A basic understanding of the DOM object model and the jQuery library is ideal but not required. No prior WebGL knowledge is expected.

WordPress for Education is full of screenshots, practical examples, step-by-step instructions, and best practices for using WordPress in an educational setting. WordPress for Education is written for educators and education personnel interested in implementing WordPress in a classroom setting. You are not required to have previous experience of WordPress or any other content management system.

Statistics, big data, and machine learning for Clojure programmers About This Book Write code using Clojure to harness the power of your data Discover the libraries and frameworks that will help you succeed A practical guide to understanding how the Clojure programming language can be used to derive insights from data Who This Book Is For This book is aimed at developers who are already productive in Clojure but who are overwhelmed by the breadth and depth of understanding required to be effective in the field of data science. Whether you’re tasked with delivering a specific analytics project or simply suspect that you could be deriving more value from your data, this book will inspire you with the opportunities–and inform you of the risks–that exist in data of all shapes and sizes. What You Will Learn Perform hypothesis testing and understand feature selection and statistical significance to interpret your results with confidence Implement the core machine learning techniques of regression, classification, clustering and recommendation Understand the importance of the value of simple statistics and distributions in exploratory data analysis Scale algorithms to web-sized datasets efficiently using distributed programming models on Hadoop and Spark Apply suitable analytic approaches for text, graph, and time series data Interpret the terminology that you will encounter in technical papers Import libraries from other JVM languages such as Java and Scala Communicate your findings clearly and convincingly to nontechnical colleagues In Detail The term “data science” has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a *ing language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist’s diverse needs. Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you’ll see how to make use of Clojure’s Java interoperability capabilities to access libraries such as Mahout and Mllib for which Clojure wrappers don’t yet exist. Even seasoned Clojure developers will develop a deeper appreciation for their language’s flexibility! You’ll learn how to apply statistical thinking to your own data and use Clojure to explore, analyze, and visualize it in a technically and statistically robust way. You can also use Incanter for local data processing and ClojureScript to present interactive visualisations and understand how distributed platforms such as Hadoop sand Spark’s MapReduce and GraphX’s BSP solve the challenges of data analysis at scale, and how to explain algorithms using those programming models. Above all, by following the explanations in this book, you’ll learn not just how to be effective using the current state-of-the-art methods in data science, but why such methods work so that you can continue to be productive as the field evolves into the future. Style and approach This is a practical guide to data science that teaches theory by example through the libraries and frameworks accessible from the Clojure programming language.

Use PhoneGap to build cross-platform mobile applications quickly and efficiently About This Book Build native mobile phone applications with HTML5, JavaScript, and CSS Incorporate smartphone capabilities such as GPS, camera, accelerometer, and more into your apps for any mobile platform Use Cordova view to embed PhoneGap into native applications to either transit smoothly to PhoneGap or incorporate PhoneGap functionalities Who This Book Is For If you are a mobile application developer in iOS or Android, or a web application developer who wants to learn how to make cross-platform mobile applications using PhoneGap, this book is perfect for you. To make the most of this book, it will be helpful if you have prior knowledge of HTML5, CSS, and JavaScript. What You Will Learn Get to grips with the fundamentals of PhoneGap to get started Set up a development environment for Linux, Mac OS, and Windows Use Cordova CLI, workflows, and Plugman Plugin manager to create mobile applications efficiently Understand the development workflow to create native cross-platform mobile applications Embed plugin support to transition to PhoneGap or use it to enhance existing applications Improve your mobile development knowledge using object-oriented programming (OOP), reusable components, and AJAX closures Be empowered to build your own mobile apps quickly with ease Discover tips and tricks to make app development fun and easy In Detail PhoneGap is an open source framework that allows you to quickly build cross-platform mobile apps using HTML5, JavaScript, and CSS. PhoneGap Build is a cloud service that allows you to quickly develop and compile mobile applications without SDKs, compilers, and hardware. PhoneGap allows you to use its existing plugins or create new ones, as per your requirements, to enhance your mobile applications. Starting by installing PhoneGap, you’ll develop an app that uses various device capabilities through different plugins and learn how to build an app in the cloud with PhoneGap’s Build service. You’ll discover how to use PhoneGap to create an application view, along with how to use a camera, geolocation, and other device capabilities to create engaging apps. Next, you’ll augment applications with PhoneGap's plugins using minimalistic code. You’ll explore the app preparation process to deploy your app to the app store. By the end of the book, you’ll have also learned how to apply hybrid mobile UIs that will work across different platforms and different screen sizes for better user experience. Style and approach This is an example-based, fast-paced guide that covers the fundamentals of creating cross-platform mobile applications with PhoneGap.

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.