Transform your Raspberry Pi into a multi-purpose web server that supports your entire multimedia world with this practical and accessible tutorial! About This Book Host websites, games, and even stream HD videos with the impressive power of Raspberry Pi 2 Get to grips with embedded programming by turning your Pi into the cloud server that can be used to power Internet of Things projects Make the Raspberry Pi 2 the center of your latest tech experiments and discover how it can manage and host resources Who This Book Is For Seeking inspiration for some new tech projectsWant to get more from your Raspberry PiThis book has been created especially for you! What You Will Learn Host your Raspberry Pi as a web server using the minimum power resources Connect your Pi to the Internet and perform network benchmarking Explore the cross-platform features of the Pi as you run Python, Node.JS, ASP.NET, and PHP all in one place Share files over the Internet using your Pi as a file server Turn your Pi into a game server, host and engage into playing Enjoy live HD video streaming and exclusive real-time text overlays In Detail There’s no end to what you can do with a Raspberry Pi – it makes a huge range of tech projects possible. This book shows you how to transform it into a multipurpose web server, able to store and manage resources that lets you build some truly innovative and impressive computing creations. You’ll learn how to use your Raspberry Pi 2 to host a website using a range of different languages, host a game server, store files, and run everything from a media center to a cloud network. If you want to take control of your technological world, start building your own server and find out what’s possible with the Raspberry Pi microcomputer. Begin by getting your Pi set up – follow each step as the book shows you how to prepare a network and configure the additional features that you’ll need to build your projects. Once you’ve done this you’ll dig a little deeper and set up your pi as a file server, making sure it’s built for speed using a range of different tools, including Python, Node.js and ASP.NET. Following this the book shows you how to extend your server to allow you to host games, and stream live HD video before customizing it even further to create a fully-fledged media center. It doesn’t stop there however – the book then dives into the exciting world of the Internet of Things (IoT). You’ll learn how to install Windows IoT onto your Raspberry Pi, the operating system that’s driving embedded software projects all around the world. Once you’ve done this you’ll be ready to explore IoT further, as the book shows you how to use your device to host a cloud network that can form the basis of a wider IoT project. Style and approach Packed with plenty of practical examples that walk you through a number of Raspberry Pi projects, this book is an accessible journey into embedded computing and Internet of Things.

Over 120 practical and easy-to-understand recipes that explain how to use Sass and Compass to write efficient, maintainable, and reusable CSS code for your web development projects About This Book Leverage Sass to make your CSS code maintainable, reusable and prevent code duplications Shorten debug time with Sass when creating complex CSS code for different browsers and devices Write easy and bullet-proof CSS with Compass using this step-by-step and detailed guide Who This Book Is For This book is mainly intended for web developers and designers who are comfortable with CSS and HTML. If you are someone with some experience with CSS, you will find the learning curve of learning Sass syntax to be less steep. Basic knowledge of web development is helpful but you don't have to be a programmer to understand Sass. What You Will Learn Spend less time debugging code Compile Sass code into readable and maintainable CSS Integrate Sass in your own projects Reuse your code to prevent code duplications Write reusable and portable CSS code Make use of pre-built and established code written by other developers Reduce development and maintenance time of your projects Set up a development environment with Gulp In Detail Sass and Compass Designer's Cookbook helps you to get most out of CSS3 and harness its benefits to create engaging and receptive applications. This book will help you develop faster and reduce the maintenance time for your web development projects by using Sass and Compass. You will learn how to use with CSS frameworks such as Bootstrap and Foundation and understand how to use other libraries of pre-built mixins. You will also learn setting up a development environment with Gulp. This book guides you through all the concepts and gives you practical examples for full understanding. Style and approach This book is the perfect mix of essential theory combined with real-life examples and problems, with clear explanations of the more sophisticated Sass concepts. Learn Sass and Compass with practical and well-explained example code. This book follows a problem and solution approach that is convenient to understand and follow.

Master the art of writing beautiful and powerful Python by using all of the features that Python 3.5 offers About This Book Become familiar with the most important and advanced parts of the Python code style Learn the trickier aspects of Python and put it in a structured context for deeper understanding of the language Offers an expert's-eye overview of how these advanced tasks fit together in Python as a whole along with practical examples Who This Book Is For Almost anyone can learn to write working * and create high quality code but they might lack a structured understanding of what it means to be 'Pythonic'. If you are a Python programmer who wants to code efficiently by getting the syntax and usage of a few intricate Python techniques exactly right, this book is for you. What You Will Learn Create a virtualenv and start a new project Understand how and when to use the functional programming paradigm Get familiar with the different ways the decorators can be written in Understand the power of generators and coroutines without digressing into lambda calculus Create metaclasses and how it makes working with Python far easier Generate HTML documentation out of documents and code using Sphinx Learn how to track and optimize application performance, both memory and cpu Use the multiprocessing library, not just locally but also across multiple machines Get a basic understanding of packaging and creating your own libraries/applications In Detail Python is a dynamic programming language. It is known for its high readability and hence it is often the first language learned by new programmers. Python being multi-paradigm, it can be used to achieve the same thing in different ways and it is compatible across different platforms. Even if you find writing Python code easy, writing code that is efficient, easy to maintain, and reuse is not so straightforward. This book is an authoritative guide that will help you learn new advanced methods in a clear and contextualised way. It starts off by creating a project-specific environment using venv, introducing you to different Pythonic syntax and common pitfalls before moving on to cover the functional features in Python. It covers how to create different decorators, generators, and metaclasses. It also introduces you to functools.wraps and coroutines and how they work. Later on you will learn to use asyncio module for asynchronous clients and servers. You will also get familiar with different testing systems such as py.test, doctest, and unittest, and debugging tools such as Python debugger and faulthandler. You will learn to optimize application performance so that it works efficiently across multiple machines and Python versions. Finally, it will teach you how to access C functions with a simple Python call. By the end of the book, you will be able to write more advanced *s and take on bigger challenges. Style and Approach This book is a comprehensive guide that covers advanced features of the Python language, and communicate them with an authoritative understanding of the underlying rationale for how, when, and why to use them.

Build websites and applications using the latest techniques in modern web development About This Book Create amazing modern day applications that run seamlessly across multiple platforms Implement multiple methodologies by creating different apps with dynamic features This unique project-based guide will help you build your own websites efficiently Who This Book Is For This book is a must-have for web developers who want to stay on top of the latest trends in web app and site development. If you are a web developer who is already familiar with HTML, CSS, and functional JavaScript, and you want to learn the latest trends in web development, this is the book for you. What You Will Learn Find out how to create responsive websites Create websites using the principals of Flat design Create deep-dive sites using parallax scrolling Discover how to use Ajax in single-page applications Create responsive navigation with CSS and JavaScript Create responsive padding with the box model property In Detail The book delivers simple instructions on how to design and build modern Web using the latest trends in web development. You will learn how to design responsive websites, created with modern Flat User Interface design patterns, build deep-scrolling websites with parallax 3D effects, and roll-your-own single-page applications. Finally, you'll work through an awesome chapter that combines them all. Each chapter features actual lines of code that you can apply right away. Style and Approach Using real-world examples, Web Design Blueprints presents practical how-to projects for site enhancements, with a light-hearted, easy-to-understand tone. This book has individual projects that cumulate until you finally build a super-project at the end, using all the skills learned

Design efficient machine learning systems that give you more accurate results About This Book Gain an understanding of the machine learning design process Optimize machine learning systems for improved accuracy Understand common programming tools and techniques for machine learning Develop techniques and strategies for dealing with large amounts of data from a variety of sources Build models to solve unique tasks Who This Book Is For This book is for data scientists, scientists, or just the curious. To get the most out of this book, you will need to know some linear algebra and some Python, and have a basic knowledge of machine learning concepts. What You Will Learn Gain an understanding of the machine learning design process Optimize the error function of your machine learning system Understand the common programming patterns used in machine learning Discover optimizing techniques that will help you get the most from your data Find out how to design models uniquely suited to your task In Detail Machine learning is one of the fastest growing trends in modern computing. It has applications in a wide range of fields, including economics, the natural sciences, web development, and business modeling. In order to harness the power of these systems, it is essential that the practitioner develops a solid understanding of the underlying design principles. There are many reasons why machine learning models may not give accurate results. By looking at these systems from a design perspective, we gain a deeper understanding of the underlying algorithms and the optimisational methods that are available. This book will give you a solid foundation in the machine learning design process, and enable you to build customised machine learning models to solve unique problems. You may already know about, or have worked with, some of the off-the-shelf machine learning models for solving common problems such as spam detection or movie classification, but to begin solving more complex problems, it is important to adapt these models to your own specific needs. This book will give you this understanding and more. Style and approach This easy-to-follow, step-by-step guide covers the most important machine learning models and techniques from a design perspective.

Build and manage networks in OpenStack using Neutron About This Book Deploy an all-in-one cloud based on OpenStack Liberty (2015.2) using RDO Learn the fundamentals of the Neutron API including networks, subnets, and ports, and how to manage these resources in the cloud Build simple virtual network infrastructures in the cloud Who This Book Is For The book is for those who are new to OpenStack and Neutron who want to learn the cloud networking fundamentals and get started with OpenStack networking. Prior networking experience along with a virtual or physical server is recommended to follow along with the concepts demonstrated in the book. What You Will Learn Install the latest Liberty (2015.2) release of OpenStack using RDO in VirtualBox Discover the basics of the Neutron API, including networks, subnets, and ports Interact with Neutron using the CLI and Horizon dashboard Create networks and subnets that provide connectivity to instances Implement software routers that connect networks and provide network address translation Secure instances using Neutron's security group functionality In Detail The OpenStack Networking API offers users the ability to create and manage both basic and complex network architectures that blend the virtual and physical network infrastructure. This book kicks off by describing various components of Openstack Neutron and installing Ubuntu OpenStack based on Canonical's process. Further on, you will use various methods to interface with Neutron to create and manage network resources. You will also get to grips with the relationship between ports, networks, and subnets through diagrams and explanations, and see how the logical components are implemented via plugins and agents. Moving forward, you will learn how virtual switches are implemented and how to build Neutron routers. You will also configure networks, subnets, and routers to provide connectivity to instances using simple examples. At the end, you will configure and manage security groups, and will observe how these rules translate to iptables rules on the host machines. By the end of the book, you will be able to build basic network architectures using Neutron networks and routers in no time. Style and approach An easy-to-follow guide that covers the networking features of OpenStack and the core Neutron API components providing a solid foundation to deploy networks and instances.

Get up and running with ReactJS by developing five cutting-edge and responsive projects About This Book Create pragmatic real-world applications while learning React and its modern developer tools Build sustainable user interfaces by transforming data into components of UI Learn how to generate reusable ReactJS components effectively Who This Book Is For If you are a web developer and wish to learn ReactJS from scratch, then this book is tailor-made for you. Good understanding of Java*, HTML, and CSS is expected. What You Will Learn Create, reuse, and compose React components using JSX Share data between various React components and techniques for data flow within a React app Handle user interactions with the help of event handlers and dynamic components Set up and use various next generation ES2015/ES6 features with React Understand the performance and immutability features of React using React add-ons Learn the techniques of Animation in React Use data stores to store model-related data and information Create a flux-based React application by using Reflux library In Detail ReactJS is an open-source JavaScript library that brings the power of reactive programming to web applications and sites. It aims to address the challenges encountered in developing single-page applications, and is intended to help developers build large, easily scalable and changing web apps. Starting with a project on Open Library API, you will be introduced to React and JSX before moving on to learning about the life cycle of a React component. In the second project, building a multi-step wizard form, you will learn about composite dynamic components and perform DOM actions. You will also learn about building a fast search engine by exploring server-side rendering in the third project on a search engine application. Next, you will build a simple frontpage for an e-commerce app in the fourth project by using data models and React add-ons. In the final project you will develop a complete social media tracker by using the flux way of defining React apps and know about the best practices and use cases with the help of ES6 and redux. By the end of this book, you will not only have a good understanding of ReactJS but will also have built your very own responsive frontend applications from scratch. Style and approach An easy-to-follow program to learn ReactJS with the help of real world projects. Each topic is explained within the context of a project and provides plenty of tips and tricks for using ReactJS.

Start building amazing projects with the Raspberry Pi right out of the box About This Book Explore the vast range of opportunities provided by Raspberry Pi and other hardware components such as a webcam, the Pi camera, and sensors Get hands-on experience with coding, networking, and hardware with the Raspberry Pi platform Learn through ample screenshots that offer a play-by-play account of how to implement Raspberry-Pi-based real-life projects Who This Book Is For What's the best way to learn how to use your Raspberry PiBy example! If you want something exciting to do whilst getting to grips with what your Pi can offer, this is the book for you. With both simple and complex projects, you'll create a wide variety of cool toys and functions with your Raspberry Pi - all with minimal coding experience necessary. What You Will Learn Set up your Raspberry Pi and get it ready for some interesting real-life projects Work with images, videos, webcams, and the Pi camera and create amazing time-lapse videos Explore the amazing world of Minecraft Pi Get to know how to use PiGlow for GPIO programming Interface your Pi with Grove Sensors and implement IoT applications Build your own cluster with Raspberry Pi Understand the networking and network programming fundamentals In Detail Want to put your Raspberry Pi through its paces right out of the boxThis tutorial guide is designed to get you learning all the tricks of the Raspberry Pi through building complete, hands-on hardware projects. Speed through the basics and then dive right in to development! Discover that you can do almost anything with your Raspberry Pi with a taste of almost everything. Get started with Pi Gaming as you learn how to set up Minecraft, and then program your own game with the help of Pygame. Turn the Pi into your own home security system with complete guidance on setting up a webcam spy camera and OpenCV computer vision for image recognition capabilities. Get to grips with GPIO programming to make a Pi-based glowing LED system, build a complete functioning motion tracker, and more. Finally, get ready to tackle projects that push your Pi to its limits. Construct a complete Internet of Things home automation system with the Raspberry Pi to control your house via Twitter; turn your Pi into a super-computer through linking multiple boards into a cluster and then add in advanced network capabilities for super speedy processing! Style and approach This step-by-step guide to building Raspberry-Pi-based projects is explained in a conversational and easy-to-follow style. Each topic is explained sequentially in the process of creating real-life projects, and detailed explanations of the basic and advanced features of various Python libraries are also included.

Improve the performance of your PHP application to ensure the application users aren't left waiting About This Book · Make the optimum use of PHP coding to improve your programming productivity · Leverage the potential of PHP for server-side programming, memory management, and object-oriented programming · Packed with real-life examples to help the readers implement concepts as they learn Who This Book Is For This book is for those who have basic experience in PHP programming. If you are developing performance-critical applications, then this book is for you. What You Will Learn · Setup high performance development and production environment for PHP 7 · Discover new OOP features in PHP 7 to achieve high performance · Improve your PHP applications' performance · Attain improved database performance · Benchmark PHP applications to optimize them · Write quality code by learning to improve code reusability, simplicity, and expressiveness · Get rid of the bottlenecks in your PHP 7 applications by writing PHP code optimally · Tackle issues related to web applications, such as high user dependency and large datasets In Detail PHP is a great language for building web applications. It is essentially a server-side *ing language that is also used for general-purpose programming. PHP 7 is the latest version, providing major backward-compatibility breaks and focusing on high performance and speed. This fast-paced introduction to PHP 7 will improve your productivity and coding skills. The concepts covered will allow you, as a PHP programmer, to improve the performance standards of your applications. We will introduce you to the new features in PHP 7 and then will run through the concepts of object-oriented programming (OOP) in PHP 7. Next, we will shed some light on how to improve your PHP 7 applications' performance and database performance. Through this book, you will be able to improve the performance of your programs using the various benchmarking tools discussed. At the end, the book discusses some best practices in PHP programming to help you improve the quality of your code. Style and approach The book is a step-by-step guide to improve the quality of your code in PHP through real-time examples. The book takes a practical approach to improving the quality of your code.

Simplify and automate server administration tasks with PowerCLI About This Book Automate VMware’s VSphere environment by learning the essentials of PowerCLI Impress your peers by developing *s to perform administration tasks Discover the intricate workings of PowerCLI through simple and real-life examples Who This Book Is For PowerCLI Essentials is focused toward virtualization professionals and system administrators who want to discover and learn about the automation techniques associated with PowerCLI for complex virtual environments. What You Will Learn Download and install PowerCLI and its basics as well as the basics of PowerShell Enchance your scritping experience Build longer *s and simpler reports Relate a task in VMware administration to a PowerCLI * Discover methods to acquire and change information remotely Set up orchestrator to manage your workflow In Detail Have you ever wished you could automatically get a report with all the relevant information about your VMware environments in exactly the format you wantOr that you could automate a crucial task that needs to be performed on a regular basisPowerful Command Line Interface (PowerCLI) *s do all these things and much more for VMware environments. PowerCLI is a command-line interface tool used to automate VMware vSphere environments. It is used to handle complicated administration tasks through use of various cmdlets and *s, which are designed to handle certain aspects of VSphere servers and to help you manage them. This book will show you the intricacies of PowerCLI through real-life examples so that you can discover the art of PowerCLI *ing. At the start, you will be taught to download and install PowerCLI and will learn about the different versions of it. Moving further, you will be introduced to the GUI of PowerCLI and will find out how to develop single line *s to duplicate running tasks, produce simple reports, and simplify administration. Next, you will learn about the methods available to get information remotely. Towards the end, you will be taught to set up orchestrator and build workflows in PowerShell with update manager and SRM *s. Style and approach Each and every topic in this book is explained in a very easy-to-follow fashion with real-life, simple examples so you’ll get an idea not only about working with PowerCLI, but will also get an idea about *ing.

Build real-world applications for the Apple Watch platform using the WatchKit framework and Swift 2.0 About This Book Find out how to download and install the Xcode development tools before learning about Xcode playgrounds and the Swift programming language Discover everything you need to know about the WatchKit platform architecture, its classes, as well its limitations This book introduces you to the very latest mobile platform with hands-on instructions so you can build your very own Apple Watch apps Who This Book Is For This book is for developers who are interested in creating amazing apps for the Apple Watch platform. Readers are expected to have no prior experience of programming. What You Will Learn Navigate within the WatchKit interface using the page-based, modal, and hierarchical navigation techniques Work with context menus to allow your users to interact with the Apple Watch and respond to their actions to perform a task Use the MapKit framework to display a map within the WatchKit interface to track the user's current location Build effective user interfaces for the WatchKit platform and integrate iCloud capabilities to synchronize data between the iOS app and the WatchKit UI Design your apps for the Apple Watch platform by adhering to the set of User Interface design guidelines set out by Apple Reinforce image caching to display animations within the Apple Watch user interface Explore WatchKit tables, which allow your users to purchase groceries and pay for them using Apple Pay Analyze the new layout system to ensure that your Apple Watch apps work with various screen sizes In Detail Wearable are the next wave of mobile technology and with the release of Apple’s WatchKit SDK, a whole new world of exciting development possibilities has opened up. Apple Watch App Development introduces you to the architecture and possibilities of the Apple Watch platform, as well as an in-depth look at how to work with Xcode playgrounds. Benefit from a rapid introduction to the Swift programming language so you can quickly begin developing apps with the WatchKit framework and the Xcode Development IDE. Get to grips with advanced topics such as notifications, glances, iCloud, Apple pay, closures, tuples, protocols, delegates, concurrency, and using Swift Playgrounds, with each concept is backed up with example code that demonstrates how to properly execute it. Finally, discover how to package and deploy your Watch application to the Apple AppStore. By the end of this book, you will have a good understanding of how to develop apps for the Apple Watch platform, and synchronize data using iCloud between the wearable and the iOS device. Style and approach This book takes a step-by-step approach to developing applications for the Apple Watch using the Swift programming language and the WatchKit UI. Each topic is explained in a conversational and easy-to-follow style.

Boost your scientific and analytic capabilities in no time at all by discovering how to build real-world applications with NumPy About This Book Optimize your Python *s with powerful NumPy modules Explore the vast opportunities to build outstanding scientific/ analytical modules by yourself Packed with rich examples to help you master NumPy arrays and universal functions Who This Book Is For If you are an experienced Python developer who intends to drive your numerical and scientific applications with NumPy, this book is for you. Prior experience or knowledge of working with the Python language is required. What You Will Learn Manipulate the key attributes and universal functions of NumPy Utilize matrix and mathematical computation using linear algebra modules Implement regression and curve fitting for models Perform time frequency / spectral density analysis using the Fourier Transform modules Collate with the distutils and setuptools modules used by other Python libraries Establish Cython with NumPy arrays Write extension modules for NumPy code using the C API Build sophisticated data structures using NumPy array with libraries such as Panda and Scikits In Detail In today’s world of science and technology, it’s all about speed and flexibility. When it comes to scientific computing, NumPy tops the list. NumPy gives you both the speed and high productivity you need. This book will walk you through NumPy using clear, step-by-step examples and just the right amount of theory. We will guide you through wider applications of NumPy in scientific computing and will then focus on the fundamentals of NumPy, including array objects, functions, and matrices, each of them explained with practical examples. You will then learn about different NumPy modules while performing mathematical operations such as calculating the Fourier Transform; solving linear systems of equations, interpolation, extrapolation, regression, and curve fitting; and evaluating integrals and derivatives. We will also introduce you to using Cython with NumPy arrays and writing extension modules for NumPy code using the C API. This book will give you exposure to the vast NumPy library and help you build efficient, high-speed programs using a wide range of mathematical features. Style and approach This quick guide will help you get to grips with the nitty-gritties of NumPy using with practical programming examples. Each topic is explained in both theoretical and practical ways with hands-on examples providing you efficient way of learning and adequate knowledge to support your professional work.

Take your Android applications to the next level of interactivity by exploring the wide variety of Android sensors About This Book Get a thorough understanding of the fundamentals and framework of Android sensors. Acquire knowledge of advance sensor programming, and learn how to connect and use sensors in external devices such as the Android Watch, Polar heart rate monitors, Adidas speed cells, and so on. Learn from real-world sensor-based applications such as the Pedometer app to detect daily steps, the Driving app to detect driving events, and the Professional Fitness tracker app to track heart rate, weight, daily steps, calories burned, and so on. Who This Book Is For This book is targeted at Android developers who want to get a good understanding of sensors and write sensor-based applications, or who want to enhance their existing applications with additional sensor functionality. A basic knowledge of Android development is required What You Will Learn Learn about sensor fundamentals, different types of sensors, and the sensor co-ordinate system Understand the various classes, callbacks, and APIs of the Android Sensor framework Check all the available sensors on an Android device and know their individual capabilities—for example, their range of values, power consumption, and so on. Implement sensor fusion using two or more sensors together and learn to compensate for the weakness of one sensor by using the strength of another Build a variety of sensor based, real-world applications such as Weather, Pedometer, Compass, Driving Events Detection, Fitness Tracker, and so on. Get to know about wake up and non-wake up sensors, wake locks, and how to use sensor batch processing along with the sensor hardware FIFO queue Develop efficient battery and processor algorithms using raw sensor data to solve real-world problems Connect to a variety of remote sensors such as body weight measurement and body fat percentage measurement using the Google Fit platform from your Android app In Detail Android phones available in today’s market have a wide variety of powerful and highly precise sensors. Interesting applications can be built with them such as a local weather app using weather sensors, analyzing risky driving behavior using motion sensors, a fitness tracker using step-counter sensors, and so on. Sensors in external devices such as Android Watch, Body Analyzer & Weight Machine, Running Speed Cell, and so on can also be connected and used from your Android app running on your phone. Moving further, this book will provide the skills required to use sensors in your Android applications. It will walk you through all the fundamentals of sensors and will provide a thorough understanding of the Android Sensor Framework. You will also get to learn how to write code for the supportive infrastructure such as background services, scheduled and long running background threads, and databases for saving sensor data. Additionally, you will learn how to connect and use sensors in external devices from your Android app using the Google Fit platform. By the end of the book, you will be well versed in the use of Android sensors and programming to build interactive applications. Style and approach A step-by-step and easy-to-follow guide that focuses on utilizing sensors to perform certain tasks. After covering the fundamentals in the first chapter, the book develops the concepts by building a real-world, sensor-based application in subsequent chapters.

Become an advanced practitioner with this progressive set of master classes on application-oriented machine learning About This Book ? Comprehensive coverage of key topics in machine learning with an emphasis on both the theoretical and practical aspects ? More than 15 open source Java tools in a wide range of techniques, with code and practical usage. ? More than 10 real-world case studies in machine learning highlighting techniques ranging from data ingestion up to analyzing the results of experiments, all preparing the user for the practical, real-world use of tools and data analysis. Who This Book Is For This book will appeal to anyone with a serious interest in topics in Data Science or those already working in related areas: ideally, intermediate-level data analysts and data scientists with experience in Java. Preferably, you will have experience with the fundamentals of machine learning and now have a desire to explore the area further, are up to grappling with the mathematical complexities of its algorithms, and you wish to learn the complete ins and outs of practical machine learning. What You Will Learn ? Master key Java machine learning libraries, and what kind of problem each can solve, with theory and practical guidance. ? Explore powerful techniques in each major category of machine learning such as classification, clustering, anomaly detection, graph modeling, and text mining. ? Apply machine learning to real-world data with methodologies, processes, applications, and analysis. ? Techniques and experiments developed around the latest specializations in machine learning, such as deep learning, stream data mining, and active and semi-supervised learning. ? Build high-performing, real-time, adaptive predictive models for batch- and stream-based big data learning using the latest tools and methodologies. ? Get a deeper understanding of technologies leading towards a more powerful AI applicable in various domains such as Security, Financial Crime, Internet of Things, social networking, and so on. In Detail Java is one of the main languages used by practicing data scientists; much of the Hadoop ecosystem is Java-based, and it is certainly the language that most production systems in Data Science are written in. If you know Java, Mastering Machine Learning with Java is your next step on the path to becoming an advanced practitioner in Data Science. This book aims to introduce you to an array of advanced techniques in machine learning, including classification, clustering, anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning. Accompanying each chapter are illustrative examples and real-world case studies that show how to apply the newly learned techniques using sound methodologies and the best Java-based tools available today. On completing this book, you will have an understanding of the tools and techniques for building powerful machine learning models to solve data science problems in just about any domain. Style and approach A practical guide to help you explore machine learning—and an array of Java-based tools and frameworks—with the help of practical examples and real-world use cases.

Build Machine Learning models with a sound statistical understanding. About This Book ? Learn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics. ? Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering. ? Master the statistical aspect of Machine Learning with the help of this example-rich guide to R and Python. Who This Book Is For This book is intended for developers with little to no background in statistics, who want to implement Machine Learning in their systems. Some programming knowledge in R or Python will be useful. What You Will Learn ? Understand the Statistical and Machine Learning fundamentals necessary to build models ? Understand the major differences and parallels between the statistical way and the Machine Learning way to solve problems ? Learn how to prepare data and feed models by using the appropriate Machine Learning algorithms from the more-than-adequate R and Python packages ? Analyze the results and tune the model appropriately to your own predictive goals ? Understand the concepts of required statistics for Machine Learning ? Introduce yourself to necessary fundamentals required for building supervised & unsupervised deep learning models ? Learn reinforcement learning and its application in the field of artificial intelligence domain In Detail Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. You will also design programs for performing tasks such as model, parameter fitting, regression, classification, density collection, and more. By the end of the book, you will have mastered the required statistics for Machine Learning and will be able to apply your new skills to any sort of industry problem. Style and approach This practical, step-by-step guide will give you an understanding of the Statistical and Machine Learning fundamentals you'll need to build models.

Use scikit-learn to apply machine learning to real-world problems About This Book ? Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks ? Learn how to build and evaluate performance of efficient models using scikit-learn ? Practical guide to master your basics and learn from real life applications of machine learning Who This Book Is For This book is intended for software engineers who want to understand how common machine learning algorithms work and develop an intuition for how to use them, and for data scientists who want to learn about the scikit-learn API. Familiarity with machine learning fundamentals and Python are helpful, but not required. What You Will Learn ? Review fundamental concepts such as bias and variance ? Extract features from categorical variables, text, and images ? Predict the values of continuous variables using linear regression and K Nearest Neighbors ? Classify documents and images using logistic regression and support vector machines ? Create ensembles of estimators using bagging and boosting techniques ? Discover hidden structures in data using K-Means clustering ? Evaluate the performance of machine learning systems in common tasks In Detail Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model. This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn’s API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model’s performance. By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach. Style and approach This book is motivated by the belief that you do not understand something until you can describe it simply. Work through toy problems to develop your understanding of the learning algorithms and models, then apply your learnings to real-life problems.

Over 80 recipes to help you breeze through your data analysis projects using R About This Book ? Analyse your data using the popular R packages like ggplot2 with ready-to-use and customizable recipes ? Find meaningful insights from your data and generate dynamic reports ? A practical guide to help you put your data analysis skills in R to practical use Who This Book Is For This book is for data scientists, analysts and even enthusiasts who want to learn and implement the various data analysis techniques using R in a practical way. Those looking for quick, handy solutions to common tasks and challenges in data analysis will find this book to be very useful. Basic knowledge of statistics and R programming is assumed. What You Will Learn ? Acquire, format and visualize your data using R ? Using R to perform an Exploratory data analysis ? Introduction to machine learning algorithms such as classification and regression ? Get started with social network analysis ? Generate dynamic reporting with Shiny ? Get started with geospatial analysis ? Handling large data with R using Spark and MongoDB ? Build Recommendation system- Collaborative Filtering, Content based and Hybrid ? Learn real world dataset examples- Fraud Detection and Image Recognition In Detail Data analytics with R has emerged as a very important focus for organizations of all kinds. R enables even those with only an intuitive grasp of the underlying concepts, without a deep mathematical background, to unleash powerful and detailed examinations of their data. This book will show you how you can put your data analysis skills in R to practical use, with recipes catering to the basic as well as advanced data analysis tasks. Right from acquiring your data and preparing it for analysis to the more complex data analysis techniques, the book will show you how you can implement each technique in the best possible manner. You will also visualize your data using the popular R packages like ggplot2 and gain hidden insights from it. Starting with implementing the basic data analysis concepts like handling your data to creating basic plots, you will master the more advanced data analysis techniques like performing cluster analysis, and generating effective analysis reports and visualizations. Throughout the book, you will get to know the common problems and obstacles you might encounter while implementing each of the data analysis techniques in R, with ways to overcoming them in the easiest possible way. By the end of this book, you will have all the knowledge you need to become an expert in data analysis with R, and put your skills to test in real-world scenarios. Style and Approach ? Hands-on recipes to walk through data science challenges using R ? Your one-stop solution for common and not-so-common pain points while performing real-world problems to execute a series of tasks. ? Addressing your common and not-so-common pain points, this is a book that you must have on the shelf

Simplify machine learning model implementations with Spark About This Book ? Solve the day-to-day problems of data science with Spark ? This unique cookbook consists of exciting and intuitive numerical recipes ? Optimize your work by acquiring, cleaning, analyzing, predicting, and visualizing your data Who This Book Is For This book is for Scala developers with a fairly good exposure to and understanding of machine learning techniques, but lack practical implementations with Spark. A solid knowledge of machine learning algorithms is assumed, as well as hands-on experience of implementing ML algorithms with Scala. However, you do not need to be acquainted with the Spark ML libraries and ecosystem. What You Will Learn ? Get to know how Scala and Spark go hand-in-hand for developers when developing ML systems with Spark ? Build a recommendation engine that scales with Spark ? Find out how to build unsupervised clustering systems to classify data in Spark ? Build machine learning systems with the Decision Tree and Ensemble models in Spark ? Deal with the curse of high-dimensionality in big data using Spark ? Implement Text analytics for Search Engines in Spark ? Streaming Machine Learning System implementation using Spark In Detail Machine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability, and optimization. Learning about algorithms enables a wide range of applications, from everyday tasks such as product recommendations and spam filtering to cutting edge applications such as self-driving cars and personalized medicine. You will gain hands-on experience of applying these principles using Apache Spark, a resilient cluster computing system well suited for large-scale machine learning tasks. This book begins with a quick overview of setting up the necessary IDEs to facilitate the execution of code examples that will be covered in various chapters. It also highlights some key issues developers face while working with machine learning algorithms on the Spark platform. We progress by uncovering the various Spark APIs and the implementation of ML algorithms with developing classification systems, recommendation engines, text analytics, clustering, and learning systems. Toward the final chapters, we’ll focus on building high-end applications and explain various unsupervised methodologies and challenges to tackle when implementing with big data ML systems. Style and approach This book is packed with intuitive recipes supported with line-by-line explanations to help you understand how to optimize your work flow and resolve problems when working with complex data modeling tasks and predictive algorithms. This is a valuable resource for data scientists and those working on large scale data projects.

Leverage Scala and Machine Learning to study and construct systems that can learn from data About This Book ? Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and updated source code in Scala ? Take your expertise in Scala programming to the next level by creating and customizing AI applications ? Experiment with different techniques and evaluate their benefits and limitations using real-world applications in a tutorial style Who This Book Is For If you’re a data scientist or a data analyst with a fundamental knowledge of Scala who wants to learn and implement various Machine learning techniques, this book is for you. All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing, and this book! What You Will Learn ? Build dynamic workflows for scientific computing ? Leverage open source libraries to extract patterns from time series ? Write your own classification, clustering, or evolutionary algorithm ? Perform relative performance tuning and evaluation of Spark ? Master probabilistic models for sequential data ? Experiment with advanced techniques such as regularization and kernelization ? Dive into neural networks and some deep learning architecture ? Apply some basic multiarm-bandit algorithms ? Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters ? Apply key learning strategies to a technical analysis of financial markets In Detail The discovery of information through data clustering and classification is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, engineering design, logistics, manufacturing, and trading strategies, to detection of genetic anomalies. The book is your one stop guide that introduces you to the functional capabilities of the Scala programming language that are critical to the creation of machine learning algorithms such as dependency injection and implicits. You start by learning data preprocessing and filtering techniques. Following this, you'll move on to unsupervised learning techniques such as clustering and dimension reduction, followed by probabilistic graphical models such as Na?ve Bayes, hidden Markov models and Monte Carlo inference. Further, it covers the discriminative algorithms such as linear, logistic regression with regularization, kernelization, support vector machines, neural networks, and deep learning. You’ll move on to evolutionary computing, multibandit algorithms, and reinforcement learning. Finally, the book includes a comprehensive overview of parallel computing in Scala and Akka followed by a de*ion of Apache Spark and its ML library. With updated codes based on the latest version of Scala and comprehensive examples, this book will ensure that you have more than just a solid fundamental knowledge in machine learning with Scala. Style and approach This book is designed as a tutorial with hands-on exercises using technical analysis of financial markets and corporate data. The approach of each chapter is such that it allows you to understand key concepts easily.

Build simple, maintainable, and easy to deploy machine learning applications. About This Book ? Build simple, but powerful, machine learning applications that leverage Go’s standard library along with popular Go packages. ? Learn the statistics, algorithms, and techniques needed to successfully implement machine learning in Go ? Understand when and how to integrate certain types of machine learning model in Go applications. Who This Book Is For This book is for Go developers who are familiar with the Go syntax and can develop, build, and run basic Go programs. If you want to explore the field of machine learning and you love Go, then this book is for you! Machine Learning with Go will give readers the practical skills to perform the most common machine learning tasks with Go. Familiarity with some statistics and math topics is necessary. What You Will Learn ? Learn about data gathering, organization, parsing, and cleaning. ? Explore matrices, linear algebra, statistics, and probability. ? See how to evaluate and validate models. ? Look at regression, classification, clustering. ? Learn about neural networks and deep learning ? Utilize times series models and anomaly detection. ? Get to grip with techniques for deploying and distributing analyses and models. ? Optimize machine learning workflow techniques In Detail The mission of this book is to turn readers into productive, innovative data analysts who leverage Go to build robust and valuable applications. To this end, the book clearly introduces the technical aspects of building predictive models in Go, but it also helps the reader understand how machine learning workflows are being applied in real-world scenarios. Machine Learning with Go shows readers how to be productive in machine learning while also producing applications that maintain a high level of integrity. It also gives readers patterns to overcome challenges that are often encountered when trying to integrate machine learning in an engineering organization. The readers will begin by gaining a solid understanding of how to gather, organize, and parse real-work data from a variety of sources. Readers will then develop a solid statistical toolkit that will allow them to quickly understand gain intuition about the content of a dataset. Finally, the readers will gain hands-on experience implementing essential machine learning techniques (regression, classification, clustering, and so on) with the relevant Go packages. Finally, the reader will have a solid machine learning mindset and a powerful Go toolkit of techniques, packages, and example implementations. Style and approach This book connects the fundamental, theoretical concepts behind Machine Learning to practical implementations using the Go programming language.

Learn the techniques used by the most successful IT people in the world. About This Book ? Get real-life case studies for different IT roles, developers, testers, analysts, project managers, DBAs ? Identify with your IT scenarios and take the right decision to move up in your career ? Improve your EQ and face any difficult scenario confidently and effectively Who This Book Is For This book is for professionals across the IT domain who work as developers, administrators, architects, administrators system analysts, and so on, who want to create a better working environment around them by improving their own emotional intelligence. This book assumes that you are a beginner to emotional intelligence and will help you understand the basic concepts before helping you with real life scenarios. What You Will Learn ? Improve your observation skills to understand people better ? Know how to identify what motivates you and those around you ? Develop strategies for working more effectively with others ? Increase your capacity to influence people and improve your communication skills ? Understand how to successfully complete tasks through other people ? Discover how to control the emotional content of your decision-making In Detail This book will help you discover your emotional quotient (EQ) through practices and techniques that are used by the most successful IT people in the world. It will make you familiar with the core skills of Emotional Intelligence, such as understanding the role that emotions play in life, especially in the workplace. You will learn to identify the factors that make your behavior consistent, not just to other employees, but to yourself. This includes recognizing, harnessing, predicting, fostering, valuing, soothing, increasing, decreasing, managing, shifting, influencing or turning around emotions and integrating accurate emotional information into decision-making, reasoning, problem solving, etc., because, emotions run business in a way that spreadsheets and logic cannot. When a deadline lurks, you’ll know the steps you need to take to keep calm and composed. You’ll find out how to meet the deadline, and not get bogged down by stress. We’ll explain these factors and techniques through real-life examples faced by IT employees and you’ll learn using the choices that they made. This book will give you a detailed analysis of the events and behavioral pattern of the employees during that time. This will help you improve your own EQ to the extent that you don’t just survive, but thrive in a competitive IT industry. Style and approach You will be taken through real-life events faced by IT employees in different scenarios. These real-world cases are analyzed along with the response of the employees, which will help you to develop your own emotion intelligence quotient and face any difficult scenario confidently and effectively.