It was written (and illustrated!) by an all-star team:David Flanagan, bestselling author of programming language "bibles" (including JavaScript: The Definitive Guide and Java in a Nutshell) and committer to the Ruby Subversion repository.Yukihiro "Matz" Matsumoto, creator, designer and lead developer of Ruby and author of Ruby in a Nutshell, which has been expanded and revised to become this book.why the lucky stiff, artist and Ruby programmer extraordinaire. This book begins with a quick-start tutorial to the language, and then explains the language in detail from the bottom up: from lexical and syntactic structure to datatypes to expressions and statements and on through methods, blocks, lambdas, closures, classes and modules. The book also includes a long and thorough introduction to the rich API of the Ruby platform, demonstrating -- with heavily-commented example code -- Ruby's facilities for text processing, numeric manipulation, collections, input/output, networking, and concurrency. An entire chapter is devoted to Ruby's metaprogramming capabilities.The Ruby Programming Language documents the Ruby language definitively but without the formality of a language specification. It is written for experienced programmers who are new to Ruby, and for current Ruby programmers who want to challenge their understanding and increase their mastery of the language.

    Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer winning in games like Jeopardy and go does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules. These approaches are too narrow to achieve genuine intelligence. The world we live in is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Marcus and Davis show us what we need to first accomplish before we get there and argue that if we are wise along the way, we won't need to worry about a future of machine overlords. If we heed their advice, humanity can create an AI that we can trust in our homes, our cars, and our doctor's offices. Reboot provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of what we can achieve and how AI can make our lives better.

    Code Craft author Pete Goodliffe presents a collection of useful techniques and approaches to the art and craft of programming that will help boost your career and your well-being.Goodliffe presents sound advice that he's learned in 15 years of professional programming. The book's standalone chapters span the range of a software developer's life--dealing with code, learning the trade, and improving performance--with no language or industry bias. Whether you're a seasoned developer, a neophyte professional, or a hobbyist, you'll find valuable tips in five independent categories:Code-level techniques for crafting lines of code, testing, debugging, and coping with complexityPractices, approaches, and attitudes: keep it simple, collaborate well, reuse, and create malleable codeTactics for learning effectively, behaving ethically, finding challenges, and avoiding stagnationPractical ways to complete things: use the right tools, know what "done" looks like, and seek help from colleaguesHabits for working well with others, and pursuing development as a social activity

    His books have been read by over 1,000,000 people and are #1 best-sellers. His book Beginning Ubuntu Linux recently entered its sixth edition, and picked-up a Linux Journal award along the way. Thomas is also the author of Ubuntu Kung Fu. * * * * * * * * * * * * * * * * * Get to grips with the Ubuntu command-line with this #1 best-selling and concise guide. "Best buck I've spent yet" — Amazon review.* Readable, accessible and easy to understand;* Learn essential Ubuntu vocational skills, or read just for fun;* Covers Ubuntu commands, syntax, the filesystem, plus advanced techniques;* For ANY version of Linux based on Debian, such as Linux Mint--not just Ubuntu!;* Includes BONUS introduction to Ubuntu chapter, plus a glossary appendix and a guide to reading Linux/Unix documentation.

    Criminals succeed by exercising enormous creativity, and those defending against them must do the same.Beautiful Security explores this challenging subject with insightful essays and analysis on topics that include:The underground economy for personal information: how it works, the relationships among criminals, and some of the new ways they pounce on their prey How social networking, cloud computing, and other popular trends help or hurt our online security How metrics, requirements gathering, design, and law can take security to a higher level The real, little-publicized history of PGP This book includes contributions from:Peiter "Mudge" Zatko Jim Stickley Elizabeth Nichols Chenxi Wang Ed Bellis Ben Edelman Phil Zimmermann and Jon Callas Kathy Wang Mark Curphey John McManus James Routh Randy V. Sabett Anton Chuvakin Grant Geyer and Brian Dunphy Peter Wayner Michael Wood and Fernando Francisco All royalties will be donated to the Internet Engineering Task Force (IETF).

    And then we wonder why software is notorious for being delivered late and full of bugs, while other engineers routinely deliver finished bridges, automobiles, electrical appliances, etc., on time and with only minor defects. This book sets out to redress this imbalance. Members of my advanced development team at Adobe who took the course based on the same material all benefited greatly from the time invested. It may appear as a highly technical text intended only for computer scientists, but it should be required reading for all practicing software engineers." --Martin Newell, Adobe Fellow"The book contains some of the most beautiful code I have ever seen." --Bjarne Stroustrup, Designer of C++"I am happy to see the content of Alex's course, the development and teaching of which I strongly supported as the CTO of Silicon Graphics, now available to all programmers in this elegant little book." --Forest Baskett, General Partner, New Enterprise Associates"Paul's patience and architectural experience helped to organize Alex's mathematical approach into a tightly-structured edifice--an impressive feat!" --Robert W. Taylor, Founder of Xerox PARC CSL and DEC Systems Research Center Elements of Programming provides a different understanding of programming than is presented elsewhere. Its major premise is that practical programming, like other areas of science and engineering, must be based on a solid mathematical foundation. The book shows that algorithms implemented in a real programming language, such as C++, can operate in the most general mathematical setting. For example, the fast exponentiation algorithm is defined to work with any associative operation. Using abstract algorithms leads to efficient, reliable, secure, and economical software.This is not an easy book. Nor is it a compilation of tips and tricks for incremental improvements in your programming skills. The book's value is more fundamental and, ultimately, more critical for insight into programming. To benefit fully, you will need to work through it from beginning to end, reading the code, proving the lemmas, and doing the exercises. When finished, you will see how the application of the deductive method to your programs assures that your system's software components will work together and behave as they must.The book presents a number of algorithms and requirements for types on which they are defined. The code for these descriptions--also available on the Web--is written in a small subset of C++ meant to be accessible to any experienced programmer. This subset is defined in a special language appendix coauthored by Sean Parent and Bjarne Stroustrup.Whether you are a software developer, or any other professional for whom programming is an important activity, or a committed student, you will come to understand what the book's experienced authors have been teaching and demonstrating for years--that mathematics is good for programming, and that theory is good for practice.

    How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.

    The authors of this collaboratively written book treat code not as merely functional but as a text—in the case of 10 PRINT, a text that appeared in many different printed sources—that yields a story about its making, its purpose, its assumptions, and more. They consider randomness and regularity in computing and art, the maze in culture, the popular BASIC programming language, and the highly influential Commodore 64 computer.

    This well-respected text offers an accessible introduction to functional programming concepts and techniques for students of mathematics and computer science. The treatment is as nontechnical as possible, and it assumes no prior knowledge of mathematics or functional programming. Cogent examples illuminate the central ideas, and numerous exercises appear throughout the text, offering reinforcement of key concepts. All problems feature complete solutions.

    In Eloquent Ruby, Russ Olsen helps you write Ruby like true Rubyists do-so you can leverage its immense, surprising power. Olsen draws on years of experience internalizing the Ruby culture and teaching Ruby to other programmers. He guides you to the "Ah Ha!" moments when it suddenly becomes clear why Ruby works the way it does, and how you can take advantage of this language's elegance and expressiveness. Eloquent Ruby starts small, answering tactical questions focused on a single statement, method, test, or bug. You'll learn how to write code that actually looks like Ruby (not Java or C#); why Ruby has so many control structures; how to use strings, expressions, and symbols; and what dynamic typing is really good for. Next, the book addresses bigger questions related to building methods and classes. You'll discover why Ruby classes contain so many tiny methods, when to use operator overloading, and when to avoid it. Olsen explains how to write Ruby code that writes its own code-and why you'll want to. He concludes with powerful project-level features and techniques ranging from gems to Domain Specific Languages. A part of the renowned Addison-Wesley Professional Ruby Series, Eloquent Ruby will help you "put on your Ruby-colored glasses" and get results that make you a true believer.

    The book focuses on techniques of lasting value and explains them precisely in terms of a simple abstract machine. The book presents all major programming paradigms in a uniform framework that shows their deep relationships and how and where to use them together.After an introduction to programming concepts, the book presents both well-known and lesser-known computation models ("programming paradigms"). Each model has its own set of techniques and each is included on the basis of its usefulness in practice. The general models include declarative programming, declarative concurrency, message-passing concurrency, explicit state, object-oriented programming, shared-state concurrency, and relational programming. Specialized models include graphical user interface programming, distributed programming, and constraint programming. Each model is based on its kernel language—a simple core language that consists of a small number of programmer- significant elements. The kernel languages are introduced progressively, adding concepts one by one, thus showing the deep relationships between different models. The kernel languages are defined precisely in terms of a simple abstract machine. Because a wide variety of languages and programming paradigms can be modeled by a small set of closely related kernel languages, this approach allows programmer and student to grasp the underlying unity of programming. The book has many program fragments and exercises, all of which can be run on the Mozart Programming System, an Open Source software package that features an interactive incremental development environment.

    But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.When AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity--operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete. Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

    It gives you hundreds of solutions to real-world problems, with clear explanations and thousands of lines of code you can use in your own projects.From data structures and algorithms, to integration with cutting-edge technologies, the Ruby Cookbook has something for every programmer. Beginners and advanced Rubyists alike will learn how to program with:Strings and numbersArrays and hashesClasses, modules, and namespacesReflection and metaprogrammingXML and HTML processingRuby on Rails (including Ajax integration)DatabasesGraphicsInternet services like email, SSH, and BitTorrentWeb servicesMultitaskingGraphical and terminal interfacesIf you need to write a web application, this book shows you how to get started with Rails. If you're a system administrator who needs to rename thousands of files, you'll see how to use Ruby for this and other everyday tasks. You'll learn how to read and write Excel spreadsheets, classify text with Bayesian filters, and create PDF files. We've even included a few silly tricks that were too cool to leave out, like how to blink the lights on your keyboard.The Ruby Cookbook is the most useful book yet written about Ruby. When you need to solve a problem, don't reinvent the wheel: look it up in the Cookbook.

    The Deitels' groundbreaking How to Program series offers unparalleled breadth and depth of programming concepts and intermediate-level topics for further study. The texts in the series feature hundreds of complete, working programs with thousands of lines of code--more than any other texts of their kind. Now, the world's best-selling Java textbook is again completely up-to- date with The Java 2 Platform Standard Edition (J2SE) 5.0.

    But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.Authors Jeremy Howard and Sylvain Gugger show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.Train models in computer vision, natural language processing, tabular data, and collaborative filteringLearn the latest deep learning techniques that matter most in practiceImprove accuracy, speed, and reliability by understanding how deep learning models workDiscover how to turn your models into web applicationsImplement deep learning algorithms from scratchConsider the ethical implications of your work