Over 40 recipes to accelerate the process of learning game design and solving development problems using Unreal EngineAbout This BookExplore the quickest way to tackle common challenges faced in Unreal EngineCreate your own content, levels, light scenes, and materials, and work with Blueprints and C++ *ingAn intermediate, fast-paced Unreal Engine guide with targeted recipes to design games within its framework Who This Book Is For This book is for those who are relatively experienced with Unreal Engine 4 and have knowledge of its fundamentals. Working knowledge of C++ is required.What You Will LearnDiscover editor functionalities for an in-depth insight into game designDevelop environments using terrain for outdoor areas and a workflow for interiors as well using brushesDesign various kinds of materials with unique features, such as mirrors and glowsExplore the various ways that lighting can be used in the engineBuild various level effects using Blueprints, Unreal's visual *ing systemSet up a development environment and develop custom functionality with C++ for your gamesCreate healthbars and main menus with animations using Slate, Unreal's UI solution, through the UMG EditorPackage and create an installer to get your project out into the world In Detail Unreal Engine is powerful tool with rich functionalities to create games. It equips you with the skills to easily build mobile and desktop games from scratch without worrying about which platform they will run on. You can focus on the individual complexities of game development such as animation and rendering. This book takes you on a journey to jumpstart your game design efforts. You will learn various aspects of the Unreal engine commonly encountered with practical examples of how it can be used, with numerous references for further study. You will start by getting acquainted with Unreal Engine 4 and building out levels for your game. This will be followed by recipes to help you create environments, place meshes, and implement your characters. You will then learn to work with lights, camera, and shadows to include special effects in your game. Moving on, you’ll learn Blueprint *ing and C++ programming to enable you to achieve trigger effects and add simple functionalities. By the end of the book, you will see how to create a healthbar and main menu, and then get your game ready to be deployed and published.Style and approach This book offers detailed, easy-to-follow recipes that will help you master a wide range of Unreal Engine 4's features. Every recipe provides step-by-step instructions, with explanations of how these features work, and alternative approaches and research materials so you can learn even more.

Navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipesAbout This BookImplement Scala in your data analysis using features from Spark, Breeze, and ZeppelinScale up your data anlytics infrastructure with practical recipes for Scala machine learningRecipes for every stage of the data analysis process, from reading and collecting data to distributed analytics Who This Book Is For This book shows data scientists and analysts how to leverage their existing knowledge of Scala for quality and scalable data analysis.What You Will LearnFamiliarize and set up the Breeze and Spark libraries and use data structuresImport data from a host of possible sources and create dataframes from CSVClean, validate and transform data using Scala to pre-process numerical and string dataIntegrate quintessential machine learning algorithms using Scala stackBundle and scale up Spark jobs by deploying them into a variety of cluster managersRun streaming and graph analytics in Spark to visualize data, enabling exploratory analysis In Detail This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits. Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you’ll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming data, as well as utilizing Spark GraphX.Style and approach This book contains a rich set of recipes that covers the full spectrum of interesting data analysis tasks and will help you revolutionize your data analysis skills using Scala and Spark.

Build robust and highly scalable web applications with Google App EngineAbout This BookGet an in-depth look at how Google App Engine works under the hoodDesign and model your application around Google's highly scalable distributed NoSQL datastore to unlock its full potentialA comprehensive guide to ensure your mastery of Google App Engine Who This Book Is For If you have been developing web applications in Python or any other dynamic language but have always wondered how to write highly scalable web applications without getting into system administration and other plumbing, then this is the book for you. No experience in writing scalable applications is required.What You Will LearnScale and develop your applications with Google App Engine's runtime environmentGet to grips with request handling mechanism and write request handlersDeep dive into Google's distributed NoSQL and highly scalable datastore and design your application around itImplement powerful search with scalable datastorePerform long-running tasks in the background using task queuesWrite compartmentalized apps using multi tenancy, memcache, and other Google App Engine runtime servicesHandle web requests using the CGI, WSGI, and multi-threaded configurationsDeploy, tweak, and manage apps in production on Google App Engine In Detail Developing web applications that serve millions of users is no easy task, as it involves a number of configurations and administrative tasks for the underlying software and hardware stack. This whole configuration requires not only expertise, but also a fair amount of time as well. Time that could have been spent on actual application functionality. Google App Engine allows you develop highly scalable web applications or backends for mobile applications without worrying about the system administration plumbing or hardware provisioning issues. Just focus writing on your business logic, the meat of the application, and let Google's powerful infrastructure scale it to thousands of requests per second and millions of users without any effort on your part. This book takes you from explaining how scalable applications work to designing and developing robust scalable web applications of your own, utilizing services available on Google App Engine. Starting with a walkthrough of scalability is and how scalable web applications work, this book introduces you to the environment under which your applications exist on Google App Engine. Next, you will learn about Google's datastore, which is a massively scalable distributed NoSQL solution built on top of BigTable. You will examine the BigTable concepts and operations in detail and reveal how it is used to build Google datastore. Armed with this knowledge, you will then advance towards how to best model your data and query that along with transactions. To augment the powerful distributed dataset, you will deep dive into search functionality offered on Google App Engine. With the search and storage sorted out, you will get a look into performing long running tasks in the background using Google App Engine task queues along with sending and receiving emails. You will also examine the memcache to boost web application performance, image processing for common image manipulation tasks. You will then explore uploading, storing, and serving large files using Blobstore and Cloud storage. Finally, you will be presented with the deployment and monitoring of your applications in production along with a detailed look at dividing applications into different working modules.Style and approach This book is an in-depth guide where you will examine the problems in the context of highly scalable web applications. This book will take you through the libraries, services, and required configuration and finally puts everything together into a small web application that showcases all the capabilities of Google App Engine.

Configure and extend Jenkins to architect, build, and automate efficient software delivery pipelinesAbout This BookConfigure and horizontally scale a Jenkins installation to support a development organization of any sizeImplement Continuous Integration, Continuous Delivery, and Continuous Deployment solutions in JenkinsA step-by-step guide to help you get the most out of the powerful automation orchestration platform that is Jenkins Who This Book Is For If you are a novice or intermediate-level Jenkins user who has used Jenkins before but are not familiar with architecting solutions and implementing it in your organization, then this is the book for you. A basic understanding of the core elements of Jenkins is required to make the best use of this book.What You Will LearnCreate and manage various types of build jobs, and implement automation tasks to support a software project of any kindGet to grips with the automated testing architecture, and scalable automated testing techniquesFacilitate the delivery of software across the SDLC by creating scalable automated deployment solutionsManage scalable automation pipelines in Jenkins using the latest build, test, and deployment strategiesImplement a scalable master / slave build automation platform, which can support Windows, Mac OSX, and Linux software solutionsCover troubleshooting and advanced configuration techniques for Jenkins slave nodesSupport a robust build and delivery system by implementing basic infrastructure as code solutions in configuration management tools such as Ansible In Detail With the software industry becoming more and more competitive, organizations are now integrating delivery automation and automated quality assurance practices into their business model. Jenkins represents a complete automation orchestration system, and can help converge once segregated groups into a cohesive product development and delivery team. By mastering the Jenkins platform and learning to architect and implement Continuous Integration, Continuous Delivery, and Continuous Deployment solutions, your organization can learn to outmanoeuvre and outpace the competition. This book will equip you with the best practices to implement advanced continuous delivery and deployment systems in Jenkins. The book begins with giving you high-level architectural fundamentals surrounding Jenkins and Continuous Integration. You will cover the different installation scenarios for Jenkins, and see how to install it as a service, as well as the advanced XML configurations. Then, you will proceed to learn more about the architecture and implementation of the Jenkins Master/Save node system, followed by creating and managing Jenkins build jobs effectively. Furthermore, you’ll explore Jenkins as an automation orchestration system, followed by implementing advanced automated testing techniques. The final chapters describe in depth the common integrations to Jenkins from third-party tools such as Jira, Artifactory, Amazon EC2, and getting the most out of the Jenkins REST-based API. By the end of this book, you will have all the knowledge necessary to be the definitive resource for managing and implementing advanced Jenkins automation solutions for your organization.Style and approach This book is a step-by-step guide to architecting and implementing automated build solutions, automated testing practices, and automated delivery methodologies. The topics covered are based on industry-proven techniques, and are explained in a simple and easy to understand manner.

Over 90 recipes to help you build and run automated tests for your web applications with Selenium WebDriverAbout This BookLearn to leverage the power of Selenium WebDriver with simple examples that illustrate real-world problems and their workaroundsExplains the testing of mobile applications with Appium for mobile platforms such as iOS and AndroidA pragmatic manual with engaging recipes and attractive screenshots to test your web applications efficiently Who This Book Is For This book is intended for software quality assurance/testing professionals, software project managers, or software developers with prior experience in using Selenium and Java to test web-based applications. This books also provides examples for C#, Python and Ruby users.What You Will LearnUnderstand how the locators work and use various locator methods to build reliable testsBuild reliable and maintainable tests with the Selenium WebDriver APIUse the PageFactory pattern to build a robust and easy to maintain test frameworkBuild data-driven tests and extend Selenium API to implement custom steps and checksIntegrate and use ATDD/BDD tools such as Cucumber, SpecFlow, Capybara, and Behave with the Selenium WebDriver APISet up iPhone/iPad and Android simulators and devices to test your mobile web application with AppiumSet up Selenium Grid for faster and parallel running of tests, increasing test coverage and reducing test execution time for cross-browser testingBuild extended Selenium WebDriver tests for additional coverage In Detail This book is an incremental guide that will help you learn and use the advanced features of the Selenium toolset including the WebDriver API in various situations to build a reliable test automation. You start off by setting up the test development environment and gain tips on the advanced locater strategy and the effective use of the Selenium WebDriver API. After that, the use of design patterns such as data - driven tests and PageFactory are demonstrated. You will then be familiarised with extending Selenium WebDriver API by implementing custom tasks and setting up your own distributed environment to run tests in parallel for cross-browser testing. Finally, we give you some tips on integrating Selenium WebDriver with other popular tools and testing mobile applications. By the end of this book, you will have learned enough to solve complex testing issues on your own.Style and approach This recipe-based guide covers real-life scenarios of testing your web apps with Selenium. Each recipe begins with a short introduction and key concepts along with illustrated examples of use cases, and ends with detailed but informative de*ions of the inner workings of the example.

Utilize the powerful ingredients of Raspberry Pi to bring to life your amazing robots that can act, draw, and have fun with laser tagsAbout This BookLearn to implement a number of features offered by Raspberry Pi to build your own amazing robotsUnderstand how to add vision and voice to your robots.This fast-paced practical guide comprises a number of creative projects to take your Raspberry Pi knowledge to the next level Who This Book Is For This all-encompassing guide was created for anyone who is interested in expanding their knowledge in applying the peripherals of Raspberry Pi. If you have a fancy for building complex-looking robots with simple, inexpensive, and readily available hardware, then this book is ideal for you. Prior understanding of Raspberry Pi with simple mechanical systems is recommended.What You Will LearnAdd sensors to your robot so that it can sense the world around itKnow everything there is to know about accessing motors and servos to provide movement to the robotic platformExplore the feature of adding vision to your robot so it can “see” the world around itRefine your robot with the skill of speech recognition so that it can receive commandsPolish your robot by adding speech output so it can communicate with the world around itMaximize the use of servos in Raspberry Pi to create a drawing robotStrengthen your robot by adding wireless communication skills so you can see what the robot is seeing and control it from a distanceBuild an unbelievable autonomous hexcopter controlled by Raspberry Pi In Detail The Raspberry Pi is a series of credit card-sized single-board computers developed in the UK by the Raspberry Pi Foundation with the intention of promoting the teaching of basic computer science in schools. The Raspberry Pi is known as a tiny computer built on a single circuit board. It runs a Linux operating system, and has connection ports for various peripherals so that it can be hooked up to sensors, motors, cameras, and more. Raspberry Pi has been hugely popular among hardware hobbyists for various projects, including robotics. This book gives you an insight into implementing several creative projects using the peripherals provided by Raspberry Pi. To start, we’ll walk through the basic robotics concepts that the world of Raspberry Pi offers us, implementing wireless communication to control your robot from a distance. Next, we demonstrate how to build a sensible and a visionary robot, maximizing the use of sensors and step controllers. After that, we focus on building a wheeled robot that can draw and play hockey. To finish with a bang, we’ll build an autonomous hexcopter, that is, a flying robot controlled by Raspberry Pi. By the end of this book, you will be a maestro in applying an array of different technologies to create almost any imaginable robot.Style and approach This book is an easy-to-follow, project-based guide that throws you directly into the action of creating almost any imaginable robot through blueprints. It is full of step by step instructions and screenshots to help you build amazing robots in no time at all.

Master the skills and techniques that are required to design, deploy, and administer real Linux-based networksAbout This BookMaster the art of using Linux and administering network services for enterprise environmentsPerform hands-on activities to reinforce expert-level knowledgeGet full coverage of both the CentOS and Debian systems, including how networking concepts differ for each Who This Book Is For Mastering Linux Network Administration is recommended for those who already understand the basics of using Linux and networking, and would like to push those skills to a higher level through real-world Linux networking scenarios. Whether you intend to run a home office consisting of Linux nodes or a rollout of a Linux network within your organization, this book is a great fit for those that desire to learn how to manage networked systems with the power of Linux.What You Will LearnInstall and configure the Debian and CentOS systemsSet up and configure file serversAdminister networked nodes remotelyDiscover how to monitor system performance for peak healthConfigure network services such as DNS and DHCPHost HTTP content via ApacheTroubleshoot Linux networking issues In Detail Linux is everywhere. Whether you run a home office, a small business, or manage enterprise systems, Linux can empower your network to perform at its very best. Armed with the advanced tools and best practice guidance of this practical guide, you'll be able to mold Linux networks to your will, empowering your systems and their users to take advantage of all that Linux-based networks have to offer. Understand how Linux networks function and get to grips with essential tips and tricks to manage them - whether you're already managing a networks, or even just starting out. With Debian and CentOS as its source, this book will divulge all the details you need to manage a real Linux-based network. With detailed activities and instructions based on real-world scenarios, this book will be your guide to the exciting world of Linux networking.Style and approach This practical guide will walk you through all the core concepts required to manage real Linux-based networks.

Learn to design, build, and deploy your Firefox OS applications, built with web technologies, to the Firefox MarketplaceAbout This BookCreate beautiful and interactive Firefox OS applications by applying your knowledge of web developmentCater your applications to a huge number of users by porting them to the Firefox OSA step-by-step learning workflow with real-life applications to demonstrate the concepts Who This Book Is For This is a practical guide that uses hands-on examples to teach you how to create applications for Firefox OS and also how to port applications to Firefox Marketplace. This book is intended for developers who want to build applications for Firefox OS. An understanding of HTML5, JavaScript, and CSS is required.What You Will LearnInstall, use, and access the Firefox OS simulator with the help of WebIDEGet to know about application manifest files and the essential difference between web applications and Firefox OS applicationsCreate an application that measures the tapping speed of the userCreate an application that allows a user to check in at a place with geolocation taggingAccess device-specific features with WebAPIs and implement these by building a photo editing and sharing applicationSubmit your own applications to the Firefox Marketplace and share them with othersProfessionally maintain the code of your application with the help of Github and deploy your hosted applications to OpenShift In Detail With broad compatibility, the latest in web technologies, and powerful development tools, Firefox is a great choice for both web developers and end users. Firefox OS’s promotion of HTML5 as a first class citizen opens up the walled gardens of mobile application development for web developers. It is because of this initiative that no special SDKs are required to develop for Firefox OS. This book will help you excel in the art of developing applications for Firefox OS. It sequentially covers knowledge building, skills acquisition, and practical applications. Starting with an introduction to Firefox OS, usage of WebIDE, and then the application structure, this book introduces applications of increasing complexity with each chapter. An application that measures your tapping speed, a geolocation tagging application, and a photo editing and sharing application are the three applications that will be built from scratch. You will learn about topics such as the difference between various types of Firefox OS applications, application manifest files, offline apps, and designing principles for applications. You will also learn to test and submit the applications to the marketplace and finally maintain the repository of the Firefox OS application. By the end, you will be able to develop beautifully designed, fully-fledged, and rigorously tested Firefox OS applications and also share them at the Firefox OS Marketplace.Style and approach This book is an easy-to-grasp workflow with practical examples of real-world applications such as Clickr, Check In!, and FotoFox. Each chapter explains the concepts, which are then reinforced as they are demonstrated in an application or a flowchart.

Create, package, and customize stunning themes using PrimeFacesAbout This BookBuild PrimeFaces themes that meet the industry standardsCustomize your themes for mobile web applications with PrimeFaces MobileA precise, example-oriented guide to help you create interesting themes using the PrimeFaces tools Who This Book Is For If you are a Web Designer who wants to create and modify PrimeFaces themes then this book is for you. Basic knowledge of JSF, CSS, and HTML is assumed.What You Will LearnUse Maven to create JSF ProjectsCreate a custom theme using JQuery UI toolsPackage your theme for distribution and use your PrimeFaces-based web applications as drop in librariesDevelop additional dynamic look and feel elements that themes do not already supplyApply look and feel elements dynamically to views without causing page refreshesReduce code repetition by applying page templates to your JSF project In Detail Developing stunning themes for web applications has never been easier! PrimeFaces delivers a powerful set of features that enables JSF developers to create and customize awesome themes on the web. It is very easy to use because it comes as a single JAR file and requires no mandatory XML configuration. With more than 30 out-of-the-box themes, jQuery integration, a mobile UI toolkit, Ajax Push technology, and much more, PrimeFaces takes JSF application development to a whole new level! This book is a hands-on example-rich guide to creating and customizing PrimeFaces themes using available tools. Beginning with creating a JSF project and integrating the PrimeFaces library, this book will introduce you to the features of theme components, how these are structured, and how PrimeFaces uses JQuery UI to apply a theme to your application. You will learn to examine and change the CSS rules and get creative by setting standard icons and adding new icons to them. You will use a combination of JavaScript and CSS to enhance your application with help of scheduler component and go on to adapt and package your custom theme so that it is compatible with the Resource Manager. Finally, you will explore PrimeFaces mobile apps, ensuring themes are compatible with your mobile applications best practices for theme design.Style and approach This book is a concise, hands-on guide to developing PrimeFaces themes, working from the ground up with examples in each topic implemented in a web application. You will be encouraged to explore areas of your own interest without the requirement to stick to the letter of the chapter.

Build real-world, industry-strength data storage solutions with time-tested design methodologies using CassandraAbout This BookExplore design patterns which co-exist with legacy data stores, migration from RDBMS, and caching technologies with CassandraLearn about design patterns and use Cassandra to provide consistency, availability, and partition tolerance guarantees for applicationsHandle temporal data for analytical purposes Who This Book Is For This book is intended for big data developers who are familiar with the basics of Cassandra and wish to understand and utilize Cassandra design patterns to develop real-world big data solutions. Prior knowledge of RDBMS solutions is assumed.What You Will LearnEnable Cassandra to co-exist with RDBMS and other legacy data storesExplore various design patterns to build effective and robust storage solutionsMigrate from RDBMS-based data stores and caching solutions to CassandraUnderstand the behaviour of Cassandra when trying to balance the needs of consistency, availability, and partition toleranceDeal with time stamps related to data effectivelySee how Cassandra can be used in analytical use casesApply the design patterns covered in this book in real-world use cases In Detail There are many NoSQL data stores used by big data applications. Cassandra is one of the most widely used NoSQL data stores that is frequently used by a huge number of heavy duty Internet-scale applications. Unlike the RDBMS world, the NoSQL landscape is very diverse and there is no one way to model data stores. This mandates the need to have good solutions to commonly seen data store design problems. Cassandra addresses such common problems simply. If you are new to Cassandra but well-versed in RDBMS modeling and design, then it is natural to model data in the same way in Cassandra, resulting in poorly performing applications and losing the real purpose of Cassandra. If you want to learn to make the most of Cassandra, this book is for you. This book starts with strategies to integrate Cassandra with other legacy data stores and progresses to the ways in which a migration from RDBMS to Cassandra can be accomplished. The journey continues with ideas to migrate data from cache solutions to Cassandra. With this, the stage is set and the book moves on to some of the most commonly seen problems in applications when dealing with consistency, availability, and partition tolerance guarantees. Cassandra is exceptionally good at dealing with temporal data and patterns such as the time-series pattern and log pattern, which are covered next. Many NoSQL data stores fail miserably when a huge amount of data is read for analytical purposes, but Cassandra is different in this regard. Keeping analytical needs in mind, you’ll walk through different and interesting design patterns. No theoretical discussions are complete without a good set of use cases to which the knowledge gained can be applied, so the book concludes with a set of use cases you can apply the patterns you’ve learned.Style and approach This book is written in very simple language and an engaging style complete with examples in every chapter and real-world use cases at the end of the book.

Learn to use powerful Python libraries for effective data processing and analysisAbout This BookLearn the basic processing steps in data analysis and how to use Python in this area through supported packages, especially Numpy, Pandas, and MatplotlibCreate, manipulate, and analyze your data to extract useful information to optimize your systemA hands-on guide to help you learn data analysis using Python Who This Book Is For If you are a Python developer who wants to get started with data analysis and you need a quick introductory guide to the python data analysis libraries, then this book is for you.What You Will LearnUnderstand the importance of data analysis and get familiar with its processing stepsGet acquainted with Numpy to use with arrays and array-oriented computing in data analysisCreate effective visualizations to present your data using MatplotlibProcess and analyze data using the time series capabilities of PandasInteract with different kind of database systems, such as file, disk format, Mongo, and RedisApply the supported Python package to data analysis applications through examplesExplore predictive analytics and machine learning algorithms using Scikit-learn, a Python library In Detail Data analysis is the process of applying logical and analytical reasoning to study each component of data. Python is a multi-domain, high-level, programming language. It’s often used as a *ing language because of its forgiving syntax and operability with a wide variety of different eco-systems. Python has powerful standard libraries or toolkits such as Pylearn2 and Hebel, which offers a fast, reliable, cross-platform environment for data analysis. With this book, we will get you started with Python data analysis and show you what its advantages are. The book starts by introducing the principles of data analysis and supported libraries, along with NumPy basics for statistic and data processing. Next it provides an overview of the Pandas package and uses its powerful features to solve data processing problems. Moving on, the book takes you through a brief overview of the Matplotlib API and some common plotting functions for DataFrame such as plot. Next, it will teach you to manipulate the time and data structure, and load and store data in a file or database using Python packages. The book will also teach you how to apply powerful packages in Python to process raw data into pure and helpful data using examples. Finally, the book gives you a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or build helpful products, such as recommendations and predictions using scikit-learn.Style and approach This is an easy-to-follow, step-by-step guide to get you familiar with data analysis and the libraries supported by Python. Topics are explained with real-world examples wherever required.

Generate effective results in a variety of visually appealing charts using the plotting packages in PythonAbout This BookExplore various tools and their strengths while building meaningful representations that can make it easier to understand dataPacked with computational methods and algorithms in diverse fields of scienceWritten in an easy-to-follow categorical style, this book discusses some niche techniques that will make your code easier to work with and reuse Who This Book Is For If you are a Python developer who performs data visualization and wants to develop existing knowledge about Python to build analytical results and produce some amazing visual display, then this book is for you. A basic knowledge level and understanding of Python libraries is assumed.What You Will LearnGather, cleanse, access, and map data to a visual frameworkRecognize which visualization method is applicable and learn best practices for data visualizationGet acquainted with reader-driven narratives and author-driven narratives and the principles of perceptionUnderstand why Python is an effective tool to be used for numerical computation much like MATLAB, and explore some interesting data structures that come with itExplore with various visualization choices how Python can be very useful in computation in the field of finance and statisticsGet to know why Python is the second choice after Java, and is used frequently in the field of machine learningCompare Python with other visualization approaches using Julia and a JavaScript-based framework such as D3.jsDiscover how Python can be used in conjunction with NoSQL such as Hive to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences. This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework, which explains the transformation of data into information and eventually knowledge, this book subsequently covers the complete visualization process using the most popular Python libraries with working examples. You will learn the usage of Numpy, Scipy, IPython, MatPlotLib, Pandas, Patsy, and Scikit-Learn with a focus on generating results that can be visualized in many different ways. Further chapters are aimed at not only showing advanced techniques such as interactive plotting; numerical, graphical linear, and non-linear regression; clustering and classification, but also in helping you understand the aesthetics and best practices of data visualization. The book concludes with interesting examples such as social networks, directed graph examples in real-life, data structures appropriate for these problems, and network analysis. By the end of this book, you will be able to effectively solve a broad set of data analysis problems.Style and approach The approach of this book is not step by step, but rather categorical. The categories are based on fields such as bioinformatics, statistical and machine learning, financial computation, and linear algebra. This approach is beneficial for the community in many different fields of work and also helps you learn how one approach can make sense across many fields

Master the art of digital forensics and analysis with PythonAbout This BookLearn to perform forensic analysis and investigations with the help of Python, and gain an advanced understanding of the various Python libraries and frameworksAnalyze Python *s to extract metadata and investigate forensic artifactsThe writers, Dr. Michael Spreitzenbarth and Dr. Johann Uhrmann, have used their experience to craft this hands-on guide to using Python for forensic analysis and investigations Who This Book Is For If you are a network security professional or forensics analyst who wants to gain a deeper understanding of performing forensic analysis with Python, then this book is for you. Some Python experience would be helpful.What You Will LearnExplore the forensic analysis of different platforms such as Windows, Android, and vSphereSemi-automatically reconstruct major parts of the system activity and time-lineLeverage Python ctypes for protocol decodingExamine artifacts from mobile, Skype, and browsersDiscover how to utilize Python to improve the focus of your analysisInvestigate in volatile memory with the help of volatility on the Android and Linux platforms In Detail Digital forensic analysis is the process of examining and extracting data digitally and examining it. Python has the combination of power, expressiveness, and ease of use that makes it an essential complementary tool to the traditional, off-the-shelf digital forensic tools. This book will teach you how to perform forensic analysis and investigations by exploring the capabilities of various Python libraries. The book starts by explaining the building blocks of the Python programming language, especially ctypes in-depth, along with how to automate typical tasks in file system analysis, common correlation tasks to discover anomalies, as well as templates for investigations. Next, we’ll show you cryptographic algorithms that can be used during forensic investigations to check for known files or to compare suspicious files with online services such as VirusTotal or Mobile-Sandbox. Moving on, you’ll learn how to sniff on the network, generate and analyze network flows, and perform log correlation with the help of Python *s and tools. You’ll get to know about the concepts of virtualization and how virtualization influences IT forensics, and you’ll discover how to perform forensic analysis of a jailbroken/rooted mobile device that is based on iOS or Android. Finally, the book teaches you how to analyze volatile memory and search for known malware samples based on YARA rules.Style and approach This easy-to-follow guide will demonstrate forensic analysis techniques by showing you how to solve real-word-scenarios step by step.

Accelerate your code writing skills with over twenty programming patterns that will make your code easier to maintain and scaleAbout This BookOptimize your web application for production useBuild views and controllers with minimal effort that will evolve with your applicationLearn how to maintain a MeteorJS project while it is running in production Who This Book Is For This book is for developers who have already had an introductory course with Meteor. Basic knowledge of web development is recommended.What You Will LearnUse of Jade, Stylus, and CoffeeScript to speed up web developmentIncrease productivity by leveraging the best packages in the communityOptimize your site for load speed with advanced publishers and subscribersLeverage the aggregation framework to produce results with big dataMaster the intricacies of front-end development using Jeet, Bootstrap, CSS animations, and moreOptimize your site for search engine visibilitySecure your site with Meteor’s best practicesTrack the live status of your application, ensuring all errors have been taken care of In Detail With the increasing interest in NodeJS web applications, a new framework, Meteor, has joined the ranks to simplify developer workflows. Meteor is one of the few open source frameworks that has received funding since its early development stages. It builds on ideas from existing frameworks and libraries, offering developers an easy way to develop a prototype app. At the same time, it gives them the tools and flexibility to build a fully fledged production app. Meteor is the weapon of choice for start-ups in today’s world. Meteor Design Patterns cuts through the jargon that most websites play with and gets to the point with simple solutions that will boost your development skills. We start off with a refresher on the basics of JavaScript programming such as templates, CoffeeScript, the Event Loop, and the Merge Box, amongst others. You then learn how to map real-world data and optimize the data’s publishers to output data with the least amount of work done by the server with some subscribe and publish patterns. Next, using front-end patterns, you will learn how to create maintainable and trackable forms, and make our site crawlable by any search engine. Following this, you will see how to optimize and secure the web application and maintain applications without breaking other features. Finally, you will learn how to deploy a secure production-ready application while learning to set up modulus, compose with Oplog tracking and SSL certificates, as well as error tracking with Kadira. Throughout the book, you will put your skills to practice and build an online shop from scratch. By the end of the book, you will have built a feature-rich online shop.Style and approach The book is a practical handbook on how to build an e-commerce web app using Meteor. Every topic ties into the webapp to easily illustrate the concepts that you are learning about.

Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problemsAbout This BookUnderstand the principles of Bayesian Inference with less mathematical equationsLearn state-of-the art Machine Learning methodsFamiliarize yourself with the recent advances in Deep Learning and Big Data frameworks with this step-by-step guide Who This Book Is For This book is for statisticians, analysts, and data scientists who want to build a Bayes-based system with R and implement it in their day-to-day models and projects. It is mainly intended for Data Scientists and Software Engineers who are involved in the development of Advanced Analytics applications. To understand this book, it would be useful if you have basic knowledge of probability theory and analytics and some familiarity with the programming language R.What You Will LearnSet up the R environmentCreate a classification model to predict and explore discrete variablesGet acquainted with Probability Theory to analyze random eventsBuild Linear Regression modelsUse Bayesian networks to infer the probability distribution of decision variables in a problemModel a problem using Bayesian Linear Regression approach with the R package BLRUse Bayesian Logistic Regression model to classify numerical dataPerform Bayesian Inference on massively large data sets using the MapReduce programs in R and Cloud computing In Detail Bayesian Inference provides a unified framework to deal with all sorts of uncertainties when learning patterns form data using machine learning models and use it for predicting future observations. However, learning and implementing Bayesian models is not easy for data science practitioners due to the level of mathematical treatment involved. Also, applying Bayesian methods to real-world problems requires high computational resources. With the recent advances in computation and several open sources packages available in R, Bayesian modeling has become more feasible to use for practical applications today. Therefore, it would be advantageous for all data scientists and engineers to understand Bayesian methods and apply them in their projects to achieve better results. Learning Bayesian Models with R starts by giving you a comprehensive coverage of the Bayesian Machine Learning models and the R packages that implement them. It begins with an introduction to the fundamentals of probability theory and R programming for those who are new to the subject. Then the book covers some of the important machine learning methods, both supervised and unsupervised learning, implemented using Bayesian Inference and R. Every chapter begins with a theoretical de*ion of the method explained in a very simple manner. Then, relevant R packages are discussed and some illustrations using data sets from the UCI Machine Learning repository are given. Each chapter ends with some simple exercises for you to get hands-on experience of the concepts and R packages discussed in the chapter. The last chapters are devoted to the latest development in the field, specifically Deep Learning, which uses a class of Neural Network models that are currently at the frontier of Artificial Intelligence. The book concludes with the application of Bayesian methods on Big Data using the Hadoop and Spark frameworks.Style and approach The book first gives you a theoretical de*ion of the Bayesian models in simple language, followed by details of its implementation in the R package. Each chapter has illustrations for the use of Bayesian model and the corresponding R package, using data sets from the UCI Machine Learning repository. Each chapter also contains sufficient exercises for you to get more hands-on practice.

Get started with Python for data analysis and numerical computing in the Jupyter notebookAbout This BookLearn the basics of Python in the Jupyter NotebookAnalyze and visualize data with pandas, NumPy, matplotlib, and seabornPerform highly-efficient numerical computations with Numba, Cython, and ipyparallel Who This Book Is For This book targets students, teachers, researchers, engineers, analysts, journalists, hobbyists, and all data enthusiasts who are interested in analyzing and visualizing real-world datasets. If you are new to programming and data analysis, this book is exactly for you. If you're already familiar with another language or analysis software, you will also appreciate this introduction to the Python data analysis platform. Finally, there are more technical topics for advanced readers. No prior experience is required; this book contains everything you need to know.What You Will LearnInstall Anaconda and code in Python in the Jupyter NotebookLoad and explore datasets interactivelyPerform complex data manipulations effectively with pandasCreate engaging data visualizations with matplotlib and seabornSimulate mathematical models with NumPyVisualize and process images interactively in the Jupyter Notebook with scikit-imageAccelerate your code with Numba, Cython, and IPython.parallelExtend the Notebook interface with HTML, JavaScript, and D3 In Detail Python is a user-friendly and powerful programming language. IPython offers a convenient interface to the language and its analysis libraries, while the Jupyter Notebook is a rich environment well-adapted to data science and visualization. Together, these open source tools are widely used by beginners and experts around the world, and in a huge variety of fields and endeavors. This book is a beginner-friendly guide to the Python data analysis platform. After an introduction to the Python language, IPython, and the Jupyter Notebook, you will learn how to analyze and visualize data on real-world examples, how to create graphical user interfaces for image processing in the Notebook, and how to perform fast numerical computations for scientific simulations with NumPy, Numba, Cython, and ipyparallel. By the end of this book, you will be able to perform in-depth analyses of all sorts of data.Style and approach This is a hands-on beginner-friendly guide to analyze and visualize data on real-world examples with Python and the Jupyter Notebook.

Over 90 practical and highly applicable recipes to successfully deploy various OpenStack configurations in productionAbout This BookGet a deep understanding of OpenStack’s internal structure and servicesLearn real-world examples on how to build and configure various production grade use cases for each of OpenStack's servicesUse a step-by-step approach to install and configure OpenStack’s services to provide Compute, Storage, and Networking as a services for cloud workloads Who This Book Is For If you have a basic understanding of Linux and Cloud computing and want to learn about configurations that OpenStack supports, this is the book for you. Knowledge of virtualization and managing Linux environments is expected. Prior knowledge or experience of OpenStack is not required, although beneficial.What You Will LearnPlan an installation of OpenStack with a basic configurationDeploy OpenStack in a highly available configurationConfigure Keystone Identity services with multiple types of identity backendsConfigure Glance Image Store with File, NFS, Swift, or Ceph image backends and use local image cachingDesign Cinder to use a single storage provider such as LVM, Ceph, and NFS backends, or to use multiple storage backends simultaneouslyManage and configure the OpenStack networking backendConfigure OpenStack's compute hypervisor and the instance scheduling mechanismBuild and customize the OpenStack dashboard In Detail OpenStack is the most popular open source cloud platform used by organizations building internal private clouds and by public cloud providers. OpenStack is designed in a fully distributed architecture to provide Infrastructure as a Service, allowing us to maintain a massively scalable cloud infrastructure. OpenStack is developed by a vibrant community of open source developers who come from the largest software companies in the world. The book provides a comprehensive and practical guide to the multiple uses cases and configurations that OpenStack supports. This book simplifies the learning process by guiding you through how to install OpenStack in a single controller configuration. The book goes deeper into deploying OpenStack in a highly available configuration. You’ll then configure Keystone Identity Services using LDAP, Active Directory, or the MySQL identity provider and configure a caching layer and SSL. After that, you will configure storage back-end providers for Glance and Cinder, which will include Ceph, NFS, Swift, and local storage. Then you will configure the Neutron networking service with provider network VLANs, and tenant network VXLAN and GRE. Also, you will configure Nova’s Hypervisor with KVM, and QEMU emulation, and you will configure Nova’s scheduler filters and weights. Finally, you will configure Horizon to use Apache HTTPD and SSL, and you will customize the dashboard’s appearance.Style and approach This book consists of clear, concise instructions coupled with practical and applicable recipes that will enable you to use and implement the latest features of OpenStack.

Utilize ServiceStack as the rock solid foundation of your distributed systemAbout This BookTake advantage of the various data providers to access authentication and authorization, sessions, cache, and databaseLeverage asynchronous processing for decoupling components to ease scalingMonitor and tune the performance of your distributed system Who This Book Is For Mastering ServiceStack is targeted at developers who have already implemented web services with ASMX, WCF, or ServiceStack and want to gain more insight into the possibilities ServiceStack has to offer to build distributed systems of all scales.What You Will LearnDesign a prudent and resilient API, following the RESTful designUnderstand the internal processing chain and utilize the provided hooksIncorporate ServiceStack as a full service provider to your existing distributed systemLeverage the power of asynchronous processing and add message queues to your architectureAnalyze and tune the performance of your service In Detail Mastering ServiceStack covers real-life problems that occur over the lifetime of a distributed system and how to solve them by deeply understanding the tools of ServiceStack. Distributed systems is the enterprise solution that provide flexibility, reliability, scaling, and performance. ServiceStack is an outstanding tool belt to create such a system in a frictionless manner, especially sophisticated designed and fun to use. The book starts with an introduction covering the essentials, but assumes you are just refreshing, are a very fast learner, or are an expert in building web services. Then, the book explains ServiceStack's data transfer object patterns and teach you how it differs from other methods of building web services with different protocols, such as SOAP and SOA. It also introduces more low-level details such as how to extend the User Auth, message queues and concepts on how the technology works. By the end of this book, you will understand the concepts, framework, issues, and resolutions related to ServiceStack.Style and approach A step-by-step approach that follows the natural requirements of a distributed system in a conversational style.

Master machine learning techniques with R to deliver insights for complex projectsAbout This BookGet to grips with the application of Machine Learning methods using an extensive set of R packagesUnderstand the benefits and potential pitfalls of using machine learning methodsImplement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML system Who This Book Is For If you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful.What You Will LearnGain deep insights to learn the applications of machine learning tools to the industryManipulate data in R efficiently to prepare it for analysisMaster the skill of recognizing techniques for effective visualization of dataUnderstand why and how to create test and training data sets for analysisFamiliarize yourself with fundamental learning methods such as linear and logistic regressionComprehend advanced learning methods such as support vector machinesRealize why and how to apply unsupervised learning methods In Detail Machine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data. The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of “Unsupervised techniques”. Finally, the book will walk you through text analysis and time series. The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems. By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages.Style and approach This is a book explains complicated concepts with easy to follow theory and real-world, practical applications. It demonstrates the power of R and machine learning extensively while highlighting the constraints.

Quickly get up to speed with MariaDB—the leading, drop-in replacement for MySQL, through this practical tutorialAbout This BookGet to know the basic SQL queries so you can quickly start using MariaDBTake control of your data through the advanced features of MariaDBExploit the full potential of MariaDB’s exclusive features through quick, practical examples Who This Book Is For If you don't know the SQL language, but you want to quickly jump into the SQL world and learn how to use MariaDB, or if you already know how to use MySQL but you want to go further, then this book is ideal for you.What You Will LearnInstall and configure MariaDBCreate databases, tables, and indexesImport and export data from and to external filesWork with views and virtual columnsCreate, read, update, and delete records in your databaseUse dynamic columnsSet up a powerful full-text search systemAccess your external data from MariaDB through the CONNECT engine In Detail This book will take you through all the nitty-gritty parts of MariaDB, right from the creation of your database all the way to using MariaDB’s advanced features. At the very beginning, we show you the basics, that is, how to install MariaDB. Then, we walk you through the databases and tables of MariaDB, and introduce SQL in MariaDB. You will learn about all the features that have been added in MariaDB but are absent in MySQL. Moving on, you’ll learn to import and export data, views, virtual columns, and dynamic columns in MariaDB. Then, you’ll get to grips with full-text searches and queries in MariaDb. You’ll also be familiarized with the CONNECT storage engine. At the end of the book, you’ll be introduced to the community of MariaDB.Style and approach This is a complete guide that uses concrete examples to help you understand and exploit the full potential of MariaDB.

Get started with Amazon S3 for virtually unlimited cloud and Internet storageAbout This BookFamiliarize yourself with the concepts of Amazon S3Understand basic operations of bucket, folders, and objects using Amazon S3 SDK JavaLeverage the power of Amazon S3 to effectively store and retrieve data Who This Book Is For This book is intended for System Engineers/ Developers, Software Architects, Project managers, and users who want to explore Amazon S3 SDK Java. If you want to learn about Amazon S3 quickly, then this book is for you. Basic knowledge of Java programming is expected.What You Will LearnStart with the basic concepts of Amazon S3 to get you goingUse Copy Object and Multipart Copy Object for objects of different sizesUnderstand how to use the amazon management console for Amazon S3Learn how to use the AWS SDK of Java and consume the Amazon S3Get to grips with managing the bucket life cycleConfigure CORS to share resources to a different domainDiscover how to develop and deploy the static website on Amazon S3 using different services of Amazon In Detail Amazon Simple Storage Service (Amazon S3), provides developers and IT teams with secure, durable, and highly-scalable object storage. Amazon S3 is easy to use, with a simple web services interface to store and retrieve any amount of data from anywhere on the web. S3 is automatically web scalable and responds to the requirements of your application and traffic, and therefore offers a key element to help companies deal dynamically with any spike in traffic for their application (such as a free e-book offer). This book starts with the basics of the Amazon S3 and its features, and you will quickly get an understanding how to use the Amazon Management Console for Amazon S3 which is the simplest way to manage Amazon S3. Next, we will cover basic operations on bucket, folder, objects. Once the basic operations are understood, you will know how to use Amazon S3 using Java SDK. Following that, you will learn about Copy Objects and Multipart copy objects for large objects size. You will also learn to manage the life cycle of bucket and how to share resources to the different domain by configuring CORS. The book will then guide you through the development and deployment of a static website on Amazon S3 using different services of Amazon. By the end of the book, you will be able to create a scalable application using Amazon S3.Style and approach This fast-paced book is a pragmatic guide to writing Amazon S3 applications. Each chapter is blended beautifully with lucid concepts and pertinent examples.