And considering that the "one man" is Neal Stephenson, "the hacker Hemingway" (Newsweek) -- acclaimed novelist, pragmatist, seer, nerd-friendly philosopher, and nationally bestselling author of groundbreaking literary works (Snow Crash, Cryptonomicon, etc., etc.) -- the word is well worth hearing. Mostly well-reasoned examination and partial rant, Stephenson's In the Beginning... was the Command Line is a thoughtful, irreverent, hilarious treatise on the cyber-culture past and present; on operating system tyrannies and downloaded popular revolutions; on the Internet, Disney World, Big Bangs, not to mention the meaning of life itself.

    . . Representing all that information is going to require a new visual language, as complex and meaningful as the great metropolitan narratives of the 19th-century novel."--from "Interface Culture"In this hip, erudite manifesto, Steven Johnson--one of the most influential people in cyberspace, according to "Newsweek" bridges the gap that yawns between technology and the arts. Drawing on his own expertise in the humanities and on the Web, he not only demonstrates how interfaces--those buttons, graphics and words on the screen through which we control information--influence our daily lives, but also tracks their roots back to Victorian novels, early cinema and even medieval urban planning. The result is a lush cultural and historical tableau in which today's interfaces take their rightful place in the lineage of artistic innovation.With "Interface Culture," Johnson brilliantly charts the vital role interface design plays in modern society. Just as the great novels of Melville, Dickens and Zola explain a rapidly industralizing society to itself, he argues, web sites, Microsoft Bob, flying toasters and the landscapes of video games tell the digital society how to imagine itself and how to get around in cyberspace's unfamiliar realm.The role once played by novelists is now fulfilled by the interface designer, who has bridged the gap between technology and everyday life by providing a conceptual framework for the vast amounts of information and computation that surround us.Johnson boldly explores the past--a terrain few tech thinkers have dared enter, and one that throws dazzling light on the modern interface's roots. From the great cathedrals of the Middle Ages to the rise of perspective drawing in the Renaissance, from Enlightenment satire to the golden age of television, "Interface Culture" uses a wealth of venerable "interface innovation" to place newfangled creations like Windows 95 and the Web in a rich historical context.Controversial, clear-sighted and challenging, "Interface Culture" also looks at the future--from what PC screens will look like in 10 years to how new interfaces will alter the style of our conversation, prose and thoughts. With a distinctively accessible style, "Interface Culture" brings new intellectual depth to the vital discussion of how technology has transformed society, and is sure to provoke wide debate in both literary and technological circles.

    But as the field evolves, designers enter the field from many disciplines. Practitioners today have enough experience in UI design that they have been exposed to design rules, but it is essential that they understand the psychology behind the rules in order to effectively apply them. In "Designing with the Mind in Mind," Jeff Johnson, author of the best selling "GUI Bloopers," provides designers with just enough background in perceptual and cognitive psychology that UI design guidelines make intuitive sense rather than being just a list of rules to follow. * The first practical, all-in-one source for practitioners on user interface design rules and why, when and how to apply them.* Provides just enough background into the reasoning behind interface design rules that practitioners can make informed decisions in every project.* Gives practitioners the insight they need to make educated design decisions when confronted with tradeoffs, including competing design rules, time constrictions, or limited resources.

    Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.But as mathematician and data scientist Cathy O'Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination--propping up the lucky, punishing the downtrodden, and undermining our democracy in the process.

    Significant numbers of poorly designed programs have been created by less-experienced developers, resulting in applications that are inefficient and hard to maintain and extend. Increasingly, software system professionals are discovering just how difficult it is to work with these inherited, non-optimal applications. For several years, expert-level object programmers have employed a growing collection of techniques to improve the structural integrity and performance of such existing software programs. Referred to as refactoring, these practices have remained in the domain of experts because no attempt has been made to transcribe the lore into a form that all developers could use... until now. In Refactoring: Improving the Design of Existing Software, renowned object technology mentor Martin Fowler breaks new ground, demystifying these master practices and demonstrating how software practitioners can realize the significant benefits of this new process.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

     At any given moment, somewhere in the world someone struggles with the same software design problems you have. You know you don't want to reinvent the wheel (or worse, a flat tire), so you look to Design Patterns--the lessons learned by those who've faced the same problems. With Design Patterns, you get to take advantage of the best practices and experience of others, so that you can spend your time on...something else. Something more challenging. Something more complex. Something more fun. You want to learn about the patterns that matter--why to use them, when to use them, how to use them (and when NOT to use them). But you don't just want to see how patterns look in a book, you want to know how they look "in the wild". In their native environment. In other words, in real world applications. You also want to learn how patterns are used in the Java API, and how to exploit Java's built-in pattern support in your own code. You want to learn the real OO design principles and why everything your boss told you about inheritance might be wrong (and what to do instead). You want to learn how those principles will help the next time you're up a creek without a design pattern. Most importantly, you want to learn the "secret language" of Design Patterns so that you can hold your own with your co-worker (and impress cocktail party guests) when he casually mentions his stunningly clever use of Command, Facade, Proxy, and Factory in between sips of a martini. You'll easily counter with your deep understanding of why Singleton isn't as simple as it sounds, how the Factory is so often misunderstood, or on the real relationship between Decorator, Facade and Adapter. With Head First Design Patterns, you'll avoid the embarrassment of thinking Decorator is something from the "Trading Spaces" show. Best of all, in a way that won't put you to sleep! We think your time is too important (and too short) to spend it struggling with academic texts. If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. Using the latest research in neurobiology, cognitive science, and learning theory, Head First Design Patterns will load patterns into your brain in a way that sticks. In a way that lets you put them to work immediately. In a way that makes you better at solving software design problems, and better at speaking the language of patterns with others on your team.

    The intended readers are programmers, architects, and project managers who have to process large amounts of data offline. Hadoop in Action will lead the reader from obtaining a copy of Hadoop to setting it up in a cluster and writing data analytic programs.The book begins by making the basic idea of Hadoop and MapReduce easier to grasp by applying the default Hadoop installation to a few easy-to-follow tasks, such as analyzing changes in word frequency across a body of documents. The book continues through the basic concepts of MapReduce applications developed using Hadoop, including a close look at framework components, use of Hadoop for a variety of data analysis tasks, and numerous examples of Hadoop in action.Hadoop in Action will explain how to use Hadoop and present design patterns and practices of programming MapReduce. MapReduce is a complex idea both conceptually and in its implementation, and Hadoop users are challenged to learn all the knobs and levers for running Hadoop. This book takes you beyond the mechanics of running Hadoop, teaching you to write meaningful programs in a MapReduce framework.This book assumes the reader will have a basic familiarity with Java, as most code examples will be written in Java. Familiarity with basic statistical concepts (e.g. histogram, correlation) will help the reader appreciate the more advanced data processing examples. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

    It reveals the visions they shared, the sacrifices they made, and the rewards they reaped.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    In a new chapter for this edition that brings the story up-to-date, Nicholas Carr revisits the dramatic new world being conjured from the circuits of the "World Wide Computer."

    Now this classic book has been fully updated and revised with leading-edge practices--and hundreds of new code samples--illustrating the art and science of software construction. Capturing the body of knowledge available from research, academia, and everyday commercial practice, McConnell synthesizes the most effective techniques and must-know principles into clear, pragmatic guidance. No matter what your experience level, development environment, or project size, this book will inform and stimulate your thinking--and help you build the highest quality code. Discover the timeless techniques and strategies that help you: Design for minimum complexity and maximum creativity Reap the benefits of collaborative development Apply defensive programming techniques to reduce and flush out errors Exploit opportunities to refactor--or evolve--code, and do it safely Use construction practices that are right-weight for your project Debug problems quickly and effectively Resolve critical construction issues early and correctly Build quality into the beginning, middle, and end of your project

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    And this may sound weirdly obvious, but every single one of those pieces of software was written by a programmer. Programmers are thus among the most quietly influential people on the planet. As we live in a world made of software, they're the architects. The decisions they make guide our behavior. When they make something newly easy to do, we do a lot more of it. If they make it hard or impossible to do something, we do less of it.If we want to understand how today's world works, we ought to understand something about coders. Who exactly are the people that are building today's world? What makes them tick? What type of personality is drawn to writing software? And perhaps most interestingly -- what does it do to them?One of the first pieces of coding a newbie learns is the program to make the computer say "Hello, world!" Like that piece of code, Clive Thompson's book is a delightful place to begin to understand this vocation, which is both a profession and a way of life, and which essentially didn't exist little more than a generation ago, but now is considered just about the only safe bet we can make about what the future holds. Thompson takes us close to some of the great coders of our time, and unpacks the surprising history of the field, beginning with the first great coders, who were women. Ironically, if we're going to traffic in stereotypes, women are arguably "naturally" better at coding than men, but they were written out of the history, and shoved out of the seats, for reasons that are illuminating. Now programming is indeed, if not a pure brotopia, at least an awfully homogenous community, which attracts people from a very narrow band of backgrounds and personality types. As Thompson learns, the consequences of that are significant - not least being a fetish for disruption at scale that doesn't leave much time for pondering larger moral issues of collateral damage. At the same time, coding is a marvelous new art form that has improved the world in innumerable ways, and Thompson reckons deeply, as no one before him has, with what great coding in fact looks like, who creates it, and where they come from. To get as close to his subject has he can, he picks up the thread of his own long-abandoned coding practice, and tries his mightiest to up his game, with some surprising results.More and more, any serious engagement with the world demands an engagement with code and its consequences, and to understand code, we must understand coders. In that regard, Clive Thompson's Hello, World! is a marvelous and delightful master class.

    In this comprehensive and readable book--already a classic statement of the aesthetics of digital media, acclaimed by practitioners and theorists alike--Janet Murray shows how the computer is reshaping the stories we live by. Murray discusses the unique properties and pleasures of digital environments and connects them with the traditional satisfactions of narrative. She analyzes the dramatic satisfaction of participatory stories and considers what would be necessary to move interactive fiction from the formats of childish games and confusing labyrinths into a mature and compelling art form. Through a blend of imagination and techno-wizardry, Murray provides both readers and writers with a guide to the storytelling of the future.