No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and more Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

    Now, he faces his most important—and difficult—audience yet. Using clear language and vivid examples, Varoufakis offers a series of letters to his young daughter about the economy: how it operates, where it came from, how it benefits some while impoverishing others. Taking bankers and politicians to task, he explains the historical origins of inequality among and within nations, questions the pervasive notion that everything has its price, and shows why economic instability is a chronic risk. Finally, he discusses the inability of market-driven policies to address the rapidly declining health of the planet his daughter’s generation stands to inherit.Throughout, Varoufakis wears his expertise lightly. He writes as a parent whose aim is to instruct his daughter on the fundamental questions of our age—and through that knowledge, to equip her against the failures and obfuscations of our current system and point the way toward a more democratic alternative.

    In this provocative, unfailingly intelligent, thoroughly researched, and surprisingly convincing big idea book, Steven Johnson draws from fields as diverse as neuroscience, economics, and media theory to argue that the pop culture we soak in every day—from Lord of the Rings to Grand Theft Auto to The Simpsons—has been growing more sophisticated with each passing year, and, far from rotting our brains, is actually posing new cognitive challenges that are actually making our minds measurably sharper. After reading Everything Bad is Good for You, you will never regard the glow of the video game or television screen the same way again. With a new afterword by the author. Steven Johnson's newest book, How We Got to Now, is now available from Riverhead Books.

    Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center.Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel, it is a joy to read. Tim Roughgarden Stanford University

    In this eloquent, persuasive book, Neil Postman alerts us to the real and present dangers of this state of affairs, and offers compelling suggestions as to how to withstand the media onslaught. Before we hand over politics, education, religion, and journalism to the show business demands of the television age, we must recognize the ways in which the media shape our lives and the ways we can, in turn, shape them to serve out highest goals.

    Who Owns the Future? is his visionary reckoning with the most urgent economic and social trend of our age: the poisonous concentration of money and power in our digital networks.Lanier has predicted how technology will transform our humanity for decades, and his insight has never been more urgently needed. He shows how Siren Servers, which exploit big data and the free sharing of information, led our economy into recession, imperiled personal privacy, and hollowed out the middle class. The networks that define our world—including social media, financial institutions, and intelligence agencies—now threaten to destroy it.But there is an alternative. In this provocative, poetic, and deeply humane book, Lanier charts a path toward a brighter future: an information economy that rewards ordinary people for what they do and share on the web.

    In Blood, Sweat, and Pixels, Jason Schreier takes readers on a fascinating odyssey behind the scenes of video game development, where the creator may be a team of 600 overworked underdogs or a solitary geek genius. Exploring the artistic challenges, technical impossibilities, marketplace demands, and Donkey Kong-sized monkey wrenches thrown into the works by corporate, Blood, Sweat, and Pixels reveals how bringing any game to completion is more than Sisyphean—it's nothing short of miraculous.Taking some of the most popular, bestselling recent games, Schreier immerses readers in the hellfire of the development process, whether it's RPG studio Bioware's challenge to beat an impossible schedule and overcome countless technical nightmares to build Dragon Age: Inquisition; indie developer Eric Barone's single-handed efforts to grow country-life RPG Stardew Valley from one man's vision into a multi-million-dollar franchise; or Bungie spinning out from their corporate overlords at Microsoft to create Destiny, a brand new universe that they hoped would become as iconic as Star Wars and Lord of the Rings—even as it nearly ripped their studio apart. Documenting the round-the-clock crunches, buggy-eyed burnout, and last-minute saves, Blood, Sweat, and Pixels is a journey through development hell—and ultimately a tribute to the dedicated diehards and unsung heroes who scale mountains of obstacles in their quests to create the best games imaginable.

    This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

    The story of information begins in a time profoundly unlike our own, when every thought and utterance vanishes as soon as it is born. From the invention of scripts and alphabets to the long-misunderstood talking drums of Africa, Gleick tells the story of information technologies that changed the very nature of human consciousness. He provides portraits of the key figures contributing to the inexorable development of our modern understanding of information: Charles Babbage, the idiosyncratic inventor of the first great mechanical computer; Ada Byron, the brilliant and doomed daughter of the poet, who became the first true programmer; pivotal figures like Samuel Morse and Alan Turing; and Claude Shannon, the creator of information theory itself. And then the information age arrives. Citizens of this world become experts willy-nilly: aficionados of bits and bytes. And we sometimes feel we are drowning, swept by a deluge of signs and signals, news and images, blogs and tweets. The Information is the story of how we got here and where we are heading.

    In How to Create a Mind, Kurzweil presents a provocative exploration of the most important project in human-machine civilization—reverse engineering the brain to understand precisely how it works and using that knowledge to create even more intelligent machines.Kurzweil discusses how the brain functions, how the mind emerges from the brain, and the implications of vastly increasing the powers of our intelligence in addressing the world’s problems. He thoughtfully examines emotional and moral intelligence and the origins of consciousness and envisions the radical possibilities of our merging with the intelligent technology we are creating.Certain to be one of the most widely discussed and debated science books of the year, How to Create a Mind is sure to take its place alongside Kurzweil’s previous classics which include Fantastic Voyage: Live Long Enough to Live Forever and The Age of Spiritual Machines.

    Loosely based on neuron behavior inside of human brains, these systems are rapidly catching up with the intelligence of their human creators, defeating the world champion Go player, achieving superhuman performance on video games, driving cars, translating languages, and sometimes even helping law enforcement fight crime. Deep Learning is a revolution that is changing every industry across the globe.Grokking Deep Learning is the perfect place to begin your deep learning journey. Rather than just learn the “black box” API of some library or framework, you will actually understand how to build these algorithms completely from scratch. You will understand how Deep Learning is able to learn at levels greater than humans. You will be able to understand the “brain” behind state-of-the-art Artificial Intelligence. Furthermore, unlike other courses that assume advanced knowledge of Calculus and leverage complex mathematical notation, if you’re a Python hacker who passed high-school algebra, you’re ready to go. And at the end, you’ll even build an A.I. that will learn to defeat you in a classic Atari game.

    Written in clear and incisive prose, The Wealth of Nations articulates the concepts indispensable to an understanding of contemporary society; and Robert Reich's Introduction both clarifies Smith's analyses and illuminates his overall relevance to the world in which we live. As Reich writes, "Smith's mind ranged over issues as fresh and topical today as they were in the late eighteenth century--jobs, wages, politics, government, trade, education, business, and ethics."Introduction by Robert Reich - Commentary by R. H. Campbell and A. S. Skinner - Includes a Modern Library Reading Group Guide

    None of these attempts succeeded, and the enterprise had been abandoned by the time the Soviet Union fell apart. Meanwhile, ARPANET, the American precursor to the Internet, went online in 1969. Why did the Soviet network, with top-level scientists and patriotic incentives, fail while the American network succeeded? In How Not to Network a Nation, Benjamin Peters reverses the usual cold war dualities and argues that the American ARPANET took shape thanks to well-managed state subsidies and collaborative research environments and the Soviet network projects stumbled because of unregulated competition among self-interested institutions, bureaucrats, and others. The capitalists behaved like socialists while the socialists behaved like capitalists.After examining the midcentury rise of cybernetics, the science of self-governing systems, and the emergence in the Soviet Union of economic cybernetics, Peters complicates this uneasy role reversal while chronicling the various Soviet attempts to build a “unified information network.” Drawing on previously unknown archival and historical materials, he focuses on the final, and most ambitious of these projects, the All-State Automated System of Management (OGAS), and its principal promoter, Viktor M. Glushkov. Peters describes the rise and fall of OGAS—its theoretical and practical reach, its vision of a national economy managed by network, the bureaucratic obstacles it encountered, and the institutional stalemate that killed it. Finally, he considers the implications of the Soviet experience for today's networked world.

    In today’s economy, we have far too much dismay along with our amazement, and technology bears some of the blame. In this combination of memoir, business strategy guide, and call to action, Tim O'Reilly, Silicon Valley’s leading intellectual and the founder of O’Reilly Media, explores the upside and the potential downsides of today's WTF? technologies. What is the future when an increasing number of jobs can be performed by intelligent machines instead of people, or done only by people in partnership with those machines? What happens to our consumer based societies—to workers and to the companies that depend on their purchasing power? Is income inequality and unemployment an inevitable consequence of technological advancement, or are there paths to a better future? What will happen to business when technology-enabled networks and marketplaces are better at deploying talent than traditional companies? How should companies organize themselves to take advantage of these new tools? What’s the future of education when on-demand learning outperforms traditional institutions? How can individuals continue to adapt and retrain? Will the fundamental social safety nets of the developed world survive the transition, and if not, what will replace them? O'Reilly is "the man who can really can make a whole industry happen," according to Eric Schmidt, Executive Chairman of Alphabet (Google.) His genius over the past four decades has been to identify and to help shape our response to emerging technologies with world shaking potential—the World Wide Web, Open Source Software, Web 2.0, Open Government data, the Maker Movement, Big Data, and now AI. O’Reilly shares the techniques he's used at O’Reilly Media  to make sense of and predict past innovation waves and applies those same techniques to provide a framework for thinking about how today’s world-spanning platforms and networks, on-demand services, and artificial intelligence are changing the nature of business, education, government, financial markets, and the economy as a whole. He provides tools for understanding how all the parts of modern digital businesses work together to create marketplace advantage and customer value, and why ultimately, they cannot succeed unless their ecosystem succeeds along with them.The core of the book's call to action is an exhortation to businesses to DO MORE with technology rather than just using it to cut costs and enrich their shareholders. Robots are going to take our jobs, they say. O'Reilly replies, “Only if that’s what we ask them to do! Technology is the solution to human problems, and we won’t run out of work till we run out of problems." Entrepreneurs need to set their sights on how they can use big data, sensors, and AI to create amazing human experiences and the economy of the future, making us all richer in the same way the tools of the first industrial revolution did. Yes, technology can eliminate labor and make things cheaper, but at its best, we use it to do things that were previously unimaginable! What is our poverty of imagination? What are the entrepreneurial leaps that will allow us to use the technology of today to build a better future, not just a more efficient one? Whether technology brings the WTF? of wonder or the WTF? of dismay isn't inevitable. It's up to us!

    They are being applied across many industries to increase profits, reduce costs, save lives and improve customer experiences. Consequently, organizations that understand these tools and know how to use them are benefiting at the expense of their rivals.Artificial Intelligence and Machine Learning for Business cuts through the hype and technical jargon that is often associated with these subjects. It delivers a simple and concise introduction for managers and business people. The focus is on practical application and how to work with technical specialists (data scientists) to maximize the benefits of these technologies.This revised and fully updated edition contains several new sections and chapters, covering a broader set of topics than before, but retains the no-nonsense style of the original.Steven Finlay is a data scientist and author with more than 20 years’ experience of developing practical, business focused, analytical solutions. He holds a PhD in management science and is an honorary research fellow at Lancaster University in the UK.