Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment. You'll not only learn how to program in R, but also how to find the right user-contributed R packages for statistical modeling, visualization, and bioinformatics.The author introduces you to the R environment, including the R graphical user interface and console, and takes you through the fundamentals of the object-oriented R language. Then, through a variety of practical examples from medicine, business, and sports, you'll learn how you can use this remarkable tool to solve your own data analysis problems.Understand the basics of the language, including the nature of R objectsLearn how to write R functions and build your own packagesWork with data through visualization, statistical analysis, and other methodsExplore the wealth of packages contributed by the R communityBecome familiar with the lattice graphics package for high-level data visualizationLearn about bioinformatics packages provided by Bioconductor"I am excited about this book. R in a Nutshell is a great introduction to R, as well as a comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it accessible to anyone working with data, not just professional statisticians."

    Siracusa's overview, wrap-up, and critique of everything new in OS X 10.10 Yosemite.

    When working hand-in-hand, they serve as the standard for the rapid development of dynamic, database-driven websites. This combination is so popular, in fact, that it's attracting manyprogramming newbies who come from a web or graphic design background and whose first language is HTML. If you fall into this ever-expanding category, then this book is for you."Learning PHP and MySQL" starts with the very basics of the PHP language, including strings and arrays, pattern matching and a detailed discussion of the variances in different PHP versions. Next, it explains how to work with MySQL, covering information on SQL data access for language and data fundamentals like tables and statements.Finally, after it's sure that you've mastered these separate concepts, the book shows you how to put them together to generate dynamic content. In the process, you'll also learn about error handling, security, HTTP authentication, and more.If you're a hobbyist who is intimidated by thick, complex computer books, then this guide definitely belongs on your shelf. "Learning PHP and MySQL" explains everything--from basic concepts to the nuts and bolts of performing specific tasks--in plain English.Part of O'Reilly's bestselling Learning series, the book is an easy-to-use resource designed specifically for newcomers. It's also a launching pad for future learning, providing you with a solid foundation for more advanced development.

    It has become adevelopment platform in it own right. Applications written using Excel are partof many corporations' core suites of business-critical applications. In spite ofthis, Excel is too often thought of as a hobbyist's platform. While there arenumerous titles on Excel and VBA, until now there have been none thatprovide an overall explanation of how to develop professional-quality Excel-basedapplications. All three authors are professional Excel developers who runtheir own companies developing Excel-based apps for clients ranging fromindividuals to the largest multinational corporations. In this book they showhow anyone from power users to professional developers can increase thespeed and usefulness of their Excel-based apps.

    Computer scientists have identified many techniques that a wide range of programs need, such as: Fuzzy pattern matching for text (identify misspellings!) Finding correlations in data Game-playing algorithms Predicting phenomena such as Web traffic Polynomial and spline fitting Using algorithms explained in this book, you too can carry out traditional programming tasks in a high-powered, efficient, easy-to-maintain manner with Perl.This book assumes a basic understanding of Perl syntax and functions, but not necessarily any background in computer science. The authors explain in a readable fashion the reasons for using various classic programming techniques, the kind of applications that use them, and -- most important -- how to code these algorithms in Perl.If you are an amateur programmer, this book will fill you in on the essential algorithms you need to solve problems like an expert. If you have already learned algorithms in other languages, you will be surprised at how much different (and often easier) it is to implement them in Perl. And yes, the book even has the obligatory fractal display program.There have been dozens of books on programming algorithms, some of them excellent, but never before has there been one that uses Perl.The authors include the editor of The Perl Journal and master librarian of CPAN; all are contributors to CPAN and have archived much of the code in this book there."This book was so exciting I lost sleep reading it." Tom Christiansen

    If programming intrigues you (for whatever reason), Beginning Programming All-In-One Desk Reference For Dummies is like having a starter programming library all in one handy, if hefty, book.In this practical guide, you'll find out about algorithms, best practices, compiling, debugging your programs, and much more. The concepts are illustrated in several different programming languages, so you'll get a feel for the variety of languages and the needs they fill.Inside you'll discover seven minibooks:Getting Started: From learning methods for writing programs to becoming familiar with types of programming languages, you'll lay the foundation for your programming adventure with this minibook. Programming Basics: Here you'll dive into how programs work, variables, data types, branching, looping, subprograms, objects, and more. Data Structures: From structures, arrays, sets, linked lists, and collections, to stacks, queues, graphs, and trees, you'll dig deeply into the data. Algorithms: This minibook shows you how to sort and search algorithms, how to use string searching, and gets into data compression and encryption. Web Programming: Learn everything you need to know about coding for the web: HyperText. Markup Language (better known simply as HTML), CSS, JavaScript, PHP, and Ruby. Programming Language Syntax: Introduces you to the syntax of various languages - C, C++, Java, C#, Perl, Python, Pascal, Delphi, Visual Basic, REALbasic - so you know when to use which one. Applications: This is the fun part where you put your newly developed programming skills to work in practical ways. Additionally, Beginning Programming All-In-One Desk Reference For Dummies shows you how to decide what you want your program to do, turn your instructions into "machine language" that the computer understands, use programming best practices, explore the "how" and "why" of data structuring, and more. And you'll get a look into various applications like database management, bioinformatics, computer security, and artificial intelligence. After you get this book and start coding, you'll soon realize that -- wow! You're a programmer!

    Madhusudhan Konda provides an overview of these, including strings in switch statements, multi-catch exception handling, try-with-resource statements, the new File System API, extensions of the JVM, support for dynamically-typed languages, and the fork and join framework for task parallelism.

    Author John Myles White shows you how this powerful class of algorithms can help you boost website traffic, convert visitors to customers, and increase many other measures of success.This is the first developer-focused book on bandit algorithms, which were previously described only in research papers. You’ll quickly learn the benefits of several simple algorithms—including the epsilon-Greedy, Softmax, and Upper Confidence Bound (UCB) algorithms—by working through code examples written in Python, which you can easily adapt for deployment on your own website.Learn the basics of A/B testing—and recognize when it’s better to use bandit algorithmsDevelop a unit testing framework for debugging bandit algorithmsGet additional code examples written in Julia, Ruby, and JavaScript with supplemental online materials

    The authors present updated coverage of compilers based on research and techniques that have been developed in the field over the past few years. The book provides a thorough introduction to compiler design and covers topics such as context-free grammars, fine state machines, and syntax-directed translation.

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

    That's what happens to many bloggers. They work hard and create great content, but there's no way their blog will succeed. Why? Because they failed to research their blog topic ahead of time. In "How to Find a Profitable Blog Topic Idea" you'll learn a proven formula for locating a winning idea that merges YOUR personal passion with something that will actually make money. Start Your Blogging Journey... Finding a great niche is one of the first steps you'll take as a blogger. That's why it's important to get it right. Everything you do online depends on locating a topic that actually has profit potential. Fortunately, it's not hard to research a blog niche. Really, it's a simple process that anyone can do - even if you don't have computer experience. Follow the Six-Step Plan for Starting a Blog "How to Find a Profitable Blog Topic Idea" provides a step-by-step strategy that can be applied TODAY. Here's what's covered: Learn the 3 B's of Demonstrating Authority Complete the Four-Step Plan for Identifying Your Passion Use Four Tools to Find a "Hook" for Your Blog Follow the Seven-Step Plan to Determine the Profit Potential of ANY Market Ask Five Simple Questions to Finalize Your Blog Decision Learn How to Make LOTS of Mistakes and Still Succeed as a Blogger It's not hard to find a great blog idea. Just follow this blueprint and you can do it today. Would You Like To Know More? Download now and locate that perfect blog idea.

    With the 97 short and extremely useful tips for programmers in this book, you'll expand your skills by adopting new approaches to old problems, learning appropriate best practices, and honing your craft through sound advice.With contributions from some of the most experienced and respected practitioners in the industry--including Michael Feathers, Pete Goodliffe, Diomidis Spinellis, Cay Horstmann, Verity Stob, and many more--this book contains practical knowledge and principles that you can apply to all kinds of projects.A few of the 97 things you should know:"Code in the Language of the Domain" by Dan North"Write Tests for People" by Gerard Meszaros"Convenience Is Not an -ility" by Gregor Hohpe"Know Your IDE" by Heinz Kabutz"A Message to the Future" by Linda Rising"The Boy Scout Rule" by Robert C. Martin (Uncle Bob)"Beware the Share" by Udi Dahan

    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.

    Cryptography is vital to keeping information safe, in an era when the formula to do so becomes more and more challenging. Written by a team of world-renowned cryptography experts, this essential guide is the definitive introduction to all major areas of cryptography: message security, key negotiation, and key management. You'll learn how to think like a cryptographer. You'll discover techniques for building cryptography into products from the start and you'll examine the many technical changes in the field.After a basic overview of cryptography and what it means today, this indispensable resource covers such topics as block ciphers, block modes, hash functions, encryption modes, message authentication codes, implementation issues, negotiation protocols, and more. Helpful examples and hands-on exercises enhance your understanding of the multi-faceted field of cryptography.An author team of internationally recognized cryptography experts updates you on vital topics in the field of cryptography Shows you how to build cryptography into products from the start Examines updates and changes to cryptography Includes coverage on key servers, message security, authentication codes, new standards, block ciphers, message authentication codes, and more Cryptography Engineering gets you up to speed in the ever-evolving field of cryptography.