As society stands on the cusp of unprecedented change, Jerry Kaplan unpacks the latest advances in robotics, machine learning, and perception powering systems that rival or exceed human capabilities. Driverless cars, robotic helpers, and intelligent agents that promote our interests have the potential to usher in a new age of affluence and leisure — but as Kaplan warns, the transition may be protracted and brutal unless we address the two great scourges of the modern developed world: volatile labor markets and income inequality. He proposes innovative, free-market adjustments to our economic system and social policies to avoid an extended period of social turmoil. His timely and accessible analysis of the promise and perils of artificial intelligence is a must-read for business leaders and policy makers on both sides of the aisle.

    These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion. These are just basic examples of the growth of Web intelligence, as increasingly sophisticated algorithms operate on the vast and growing amount of data on the Web, sifting, selecting, comparing, aggregating, correcting; following simple but powerful rules to decide what matters. While original optimism for Artificial Intelligence declined, this new kind of machine intelligence is emerging as the Web grows ever larger and more interconnected.Gautam Shroff takes us on a journey through the computer science of search, natural language, text mining, machine learning, swarm computing, and semantic reasoning, from Watson to self-driving cars. This machine intelligence may even mimic at a basic level what happens in the brain.

    The world is more complex and volatile today than at any other time in our history. The tools of our modern existence are getting faster, cheaper, and smaller at an exponential rate, transforming every aspect of society, from business to culture and from the public sphere to our most private moments. The people who succeed will be the ones who learn to think differently. In Whiplash, Joi Ito and Jeff Howe distill that logic into nine organizing principles for navigating and surviving this tumultuous period: Emergence over AuthorityPull over PushCompasses over MapsRisk over SafetyDisobedience over CompliancePractice over TheoryDiversity over AbilityResilience over StrengthSystems over Objects Filled with incredible case studies and cutting-edge research and philosophies from the MIT Media Lab and beyond, Whiplash will help you adapt and succeed in this unpredictable world.

    If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills

    It covers topics ranging from personal responsibility and career development to architectural techniques for keeping your code flexible and easy to adapt and reuse. Read this book, and you'll learn how toFight software rot; Avoid the trap of duplicating knowledge; Write flexible, dynamic, and adaptable code; Avoid programming by coincidence; Bullet-proof your code with contracts, assertions, and exceptions; Capture real requirements; Test ruthlessly and effectively; Delight your users; Build teams of pragmatic programmers; and Make your developments more precise with automation. Written as a series of self-contained sections and filled with entertaining anecdotes, thoughtful examples, and interesting analogies, The Pragmatic Programmer illustrates the best practices and major pitfalls of many different aspects of software development. Whether you're a new coder, an experienced programmer, or a manager responsible for software projects, use these lessons daily, and you'll quickly see improvements in personal productivity, accuracy, and job satisfaction. You'll learn skills and develop habits and attitudes that form the foundation for long-term success in your career. You'll become a Pragmatic Programmer.

    His breaking of the German U-boat Enigma cipher in World War II ensured Allied-American control of the Atlantic. But Turing's vision went far beyond the desperate wartime struggle. Already in the 1930s he had defined the concept of the universal machine, which underpins the computer revolution. In 1945 he was a pioneer of electronic computer design. But Turing's true goal was the scientific understanding of the mind, brought out in the drama and wit of the famous "Turing test" for machine intelligence and in his prophecy for the twenty-first century.Drawn in to the cockpit of world events and the forefront of technological innovation, Alan Turing was also an innocent and unpretentious gay man trying to live in a society that criminalized him. In 1952 he revealed his homosexuality and was forced to participate in a humiliating treatment program, and was ever after regarded as a security risk. His suicide in 1954 remains one of the many enigmas in an astonishing life story.

    (Marginal cost is the cost of producing additional units of a good or service, if fixed costs are not counted.) While economists have always welcomed a reduction in marginal cost, they never anticipated the possibility of a technological revolution that might bring marginal costs to near zero, making goods and services priceless, nearly free, and abundant, and no longer subject to market forces.Now, a formidable new technology infrastructure—the Internet of things (IoT)—is emerging with the potential of pushing large segments of economic life to near zero marginal cost in the years ahead. Rifkin describes how the Communication Internet is converging with a nascent Energy Internet and Logistics Internet to create a new technology platform that connects everything and everyone. Billions of sensors are being attached to natural resources, production lines, the electricity grid, logistics networks, recycling flows, and implanted in homes, offices, stores, vehicles, and even human beings, feeding Big Data into an IoT global neural network. Prosumers can connect to the network and use Big Data, analytics, and algorithms to accelerate efficiency, dramatically increase productivity, and lower the marginal cost of producing and sharing a wide range of products and services to near zero, just like they now do with information goods.The plummeting of marginal costs is spawning a hybrid economy—part capitalist market and part Collaborative Commons—with far reaching implications for society, according to Rifkin. Hundreds of millions of people are already transferring parts of their economic lives to the global Collaborative Commons. Prosumers are plugging into the fledgling IoT and making and sharing their own information, entertainment, green energy, and 3D-printed products at near zero marginal cost. They are also sharing cars, homes, clothes and other items via social media sites, rentals, redistribution clubs, and cooperatives at low or near zero marginal cost. Students are enrolling in free massive open online courses (MOOCs) that operate at near zero marginal cost. Social entrepreneurs are even bypassing the banking establishment and using crowdfunding to finance startup businesses as well as creating alternative currencies in the fledgling sharing economy. In this new world, social capital is as important as financial capital, access trumps ownership, sustainability supersedes consumerism, cooperation ousts competition, and "exchange value" in the capitalist marketplace is increasingly replaced by "sharable value" on the Collaborative Commons.Rifkin concludes that capitalism will remain with us, albeit in an increasingly streamlined role, primarily as an aggregator of network services and solutions, allowing it to flourish as a powerful niche player in the coming era. We are, however, says Rifkin, entering a world beyond markets where we are learning how to live together in an increasingly interdependent global Collaborative Commons.

    This book surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use.The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts.The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants.Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.

    individual whose contributions to the scientific, business and cultural realms are extensive."—BookpageBefore slim laptops that fit into briefcases, computers looked like strange, alien vending machines. But in "the most staggering burst of technical invention by a single person in high-tech history" (BusinessWeek​) Steve Wozniak invented the first true personal computer. Wozniak teamed up with Steve Jobs, and Apple Computer was born, igniting the computer revolution and transforming the world. Here, thirty years later, the mischievous genius with the low profile treats readers to a rollicking, no-holds-barred account of his life—for once, in the voice of the wizard himself.

    Jill Lepore, best-selling author of These Truths, came across the company’s papers in MIT’s archives and set out to tell this forgotten history, the long-lost backstory to the methods, and the arrogance, of Silicon Valley.Founded in 1959 by some of the nation’s leading social scientists—“the best and the brightest, fatally brilliant, Icaruses with wings of feathers and wax, flying to the sun”—Simulmatics proposed to predict and manipulate the future by way of the computer simulation of human behavior. In summers, with their wives and children in tow, the company’s scientists met on the beach in Long Island under a geodesic, honeycombed dome, where they built a “People Machine” that aimed to model everything from buying a dishwasher to counterinsurgency to casting a vote. Deploying their “People Machine” from New York, Washington, Cambridge, and even Saigon, Simulmatics’ clients included the John F. Kennedy presidential campaign, the New York Times, the Department of Defense, and dozens of major manufacturers: Simulmatics had a hand in everything from political races to the Vietnam War to the Johnson administration’s ill-fated attempt to predict race riots. The company’s collapse was almost as rapid as its ascent, a collapse that involved failed marriages, a suspicious death, and bankruptcy. Exposed for false claims, and even accused of war crimes, it closed its doors in 1970 and all but vanished. Until Lepore came across the records of its remains.The scientists of Simulmatics believed they had invented “the A-bomb of the social sciences.” They did not predict that it would take decades to detonate, like a long-buried grenade. But, in the early years of the twenty-first century, that bomb did detonate, creating a world in which corporations collect data and model behavior and target messages about the most ordinary of decisions, leaving people all over the world, long before the global pandemic, crushed by feelings of helplessness. This history has a past; If Then is its cautionary tale.

    Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays. This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.

    In it, developer and life coach John Sonmez addresses a wide range of important "soft" topics, from career and productivity to personal finance and investing, and even fitness and relationships, all from a developer-centric viewpoint.For most software developers, coding is the fun part. The hard bits are dealing with clients, peers, and managers, staying productive, achieving financial security, keeping yourself in shape, and finding true love. This book is here to help.Soft Skills: The software developer's life manual is a guide to a well-rounded, satisfying life as a technology professional. In it, developer and life coach John Sonmez offers advice to developers on important "soft" subjects like career and productivity, personal finance and investing, and even fitness and relationships. Arranged as a collection of 71 short chapters, this fun-to-read book invites you to dip in wherever you like. A Taking Action section at the end of each chapter shows you how to get quick results. Soft Skills will help make you a better programmer, a more valuable employee, and a happier, healthier person.What's InsideBoost your career by building a personal brandJohn's secret ten-step process for learning quicklyFitness advice to turn your geekiness to your advantageUnique strategies for investment and early retirement

    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.

    Sipser's candid, crystal-clear style allows students at every level to understand and enjoy this field. His innovative "proof idea" sections explain profound concepts in plain English. The new edition incorporates many improvements students and professors have suggested over the years, and offers updated, classroom-tested problem sets at the end of each chapter.