Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

    

    The book s two-part coverage organizes topics under basic theory, and assembles an arsenal of approximation schemes with illustrative applications. For physicists and engineers. "

    In this handbook, data expert Q. Ethan McCallum has gathered 19 colleagues from every corner of the data arena to reveal how they’ve recovered from nasty data problems.From cranky storage to poor representation to misguided policy, there are many paths to bad data. Bottom line? Bad data is data that gets in the way. This book explains effective ways to get around it.Among the many topics covered, you’ll discover how to:Test drive your data to see if it’s ready for analysisWork spreadsheet data into a usable formHandle encoding problems that lurk in text dataDevelop a successful web-scraping effortUse NLP tools to reveal the real sentiment of online reviewsAddress cloud computing issues that can impact your analysis effortAvoid policies that create data analysis roadblocksTake a systematic approach to data quality analysis

    Written by the lead technical writer at one of Silicon Valley's most exciting companies, Modern Technical Writing is a set of guiding principles and thoughtful recommendations for new and experienced technical writers alike. Not a reference manual, and not comprehensive, it instead serves as an introduction to a sensible writing and publishing process, one that has eluded the profession for too long.

    Jonathan Stark shows you how to leverage your existing web development skills to build native iPhone applications using these technologies." --John Allsopp, author and founder of Web Directions"Jonathan's book is the most comprehensive documentation available for developing web applications for mobile Safari. Not just great tech coverage, this book is an easy read of purely fascinating mobile tidbits in a fun colloquial style. Must have for all PhoneGap developers." -- Brian LeRoux, Nitobi SoftwareIt's a fact: if you know HTML, CSS, and JavaScript, you already have the tools you need to develop your own iPhone apps. With this book, you'll learn how to use these open source web technologies to design and build apps for the iPhone and iPod Touch on the platform of your choice-without using Objective-C or Cocoa.Device-agnostic mobile apps are the wave of the future, and this book shows you how to create one product for several platforms. You'll find guidelines for converting your product into a native iPhone app using the free PhoneGap framework. And you'll learn why releasing your product as a web app first helps you find, fix, and test bugs much faster than if you went straight to the App Store with a product built with Apple's tools.Build iPhone apps with tools you already know how to useLearn how to make an existing website look and behave like an iPhone appAdd native-looking animations to your web app using jQTouchTake advantage of client-side data storage with apps that run even when the iPhone is offlineHook into advanced iPhone features -- including the accelerometer, geolocation, and vibration -- with JavaScriptSubmit your applications to the App Store with XcodeThis book received valuable community input through O'Reilly's Open Feedback Publishing System (OFPS). Learn more at http://labs.oreilly.com/ofps.html.

    But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.Topics include:Statistical inference, exploratory data analysis, and the data science processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and HadoopDoing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

    Written by a panel of expert authors, the book covers every aspect of Drupal, from planning a successful project all the way up to making a living from designing Drupal sites and to contributing to the Drupal community yourself. With this book you will:Follow practical approaches to solving many online communication needs with Drupal with real examples. Learn how to keep learning about Drupal: administration, development, theming, design, and architecture. Go beyond the code to engage with the Drupal community as a contributing member and to do Drupal sustainably as a business.The Definitive Guide to Drupal 7 was written by the following team of expert Drupal authors:Benjamin Melançon, Jacine Luisi, Károly Négyesi, Greg Anderson, Bojhan Somers, Stéphane Corlosquet, Stefan Freudenberg, Michelle Lauer, Ed Carlevale, Florian Lorétan, Dani Nordin, Ryan Szrama, Susan Stewart, Jake Strawn, Brian Travis, Dan Hakimzadeh, Amye Scavarda, Albert Albala, Allie Micka, Robert Douglass, Robin Monks, Roy Scholten, Peter Wolanin, Kay VanValkenburgh, Greg Stout, Kasey Qynn Dolin, Mike Gifford, Claudina Sarahe, Sam Boyer, and Forest Mars, with contributions from George Cassie, Mike Ryan, Nathaniel Catchpole, and Dmitri Gaskin.For more information, check out the Drupaleasy podcast #63, in which author Benjamin Melançon discusses The Definitive Guide to Drupal 7 in great detail:http: //drupaleasy.com/podcast/2011/08/drupal...

    Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

    You’ll quickly discover the many advantages of the language, including access to all the great tools and libraries of the .NET platform.Reap the benefits of functional programming for your next project, whether you’re writing concurrent code, or building data- or math-intensive applications. With this comprehensive book, former F# team member Chris Smith gives you a head start on the fundamentals and walks you through advanced concepts of the F# language.Learn F#’s unique characteristics for building applicationsGain a solid understanding of F#’s core syntax, including object-oriented and imperative stylesMake your object-oriented code better by applying functional programming patternsUse advanced functional techniques, such as tail-recursion and computation expressionsTake advantage of multi-core processors with asynchronous workflows and parallel programmingUse new type providers for interacting with web services and information-rich environmentsLearn how well F# works as a scripting language

    Servers give sysadmins a incredible visibility into the network—once they know how to unlock it. Most sysadmins don’t need to understand window scaling, or the differences between IPv4 and IPv6 echo requests, or other intricacies of the TCP/IP protocols. You need only enough to deploy your own applications and get easy support from the network team.This book teaches you:•How modern networks really work•The essentials of TCP/IP•The next-generation protocol, IPv6•The right tools to diagnose network problems, and how to use them•Troubleshooting everything from the physical wire to DNS•How to see the traffic you send and receive•Connectivity testing•How to communicate with your network team to quickly resolve problemsA systems administrator doesn’t need to know the innards of TCP/IP, but knowing enough to diagnose your own network issues transforms a good sysadmin into a great one.

    

    

    New languages, new frameworks, new ways of doing things - a constant struggle just to stay current in the industry. This left no time to learn the foundational concepts and skills that come with a degree in Computer Science.

    Thoroughly updated to include Java 6, the Third Edition of Horstmann's bestselling text helps you absorb computing concepts and programming principles, develop strong problem-solving skills, and become a better programmer, all while exploring the elements of Java that are needed to write real-life programs. A top-notch introductory text for beginners, Big Java, Third Edition is also a thorough reference for students and professionals alike to Java technologies, Internet programming, database access, and many other areas of computer science.Features of the Third Edition: The 'Objects Gradual' approach leads you into object-oriented thinking step-by-step, from using classes, implementing simple methods, all the way to designing your own object-oriented programs. A strong emphasis on test-driven development encourages you to consider outcomes as you write programming code so you design better, more usable programs Helpful "Testing Track" introduces techniques and tools step by step, ensuring that you master one before moving on to the next New teaching and learning tools in WileyPLUS--including a unique assignment checker that enables you to test your programming problems online before you submit them for a grade Graphics topics are developed gradually throughout the text, conveniently highlighted in separate color-coded sections Updated coverage is fully compatible with Java 5 and includes a discussion of the latest Java 6 features