It can help us do things faster and more efficiently than ever before, from tracking wolves through Minnesota by GPS to predicting which crimes are likely to happen where. Mega data has led to scientific and social achievements that would have been impossible just a few years ago. But being too dazzled by the scale, the speed, and the geeky jargon can lead us astray. It's big, but it's not always clever.Timandra Harkness cuts through the hype to put data science into its real-life context using a wide range of stories, people, and places to reveal what is essentially a human science--demystifying big data, telling us where it comes from and what it can do. BIG DATA then asks the awkward questions: What are the unspoken assumptions underlying its methods? Are we being bamboozled by mega data's size, its speed, and its shiny technology?Nobody needs a degree in computer science to follow Harkness's exploration of what mega data can do for us--and what it can't or shouldn't. BIG DATA asks you to decide: Are you a data point, or a human being?

    William Mitchell makes extensive use of practical examples and illustrations in a technically well-grounded yet accessible examination of architecture and urbanism in the context of the digital telecommunications revolution, the ongoing miniaturization of electronics, the commodification of bits, and the growing domination of software over materialized form.

    There are many positive ways in which the Internet has contributed to the world, but as a society we are less aware of the Internet’s deeply negative effects on our psychology, economy, and culture. In The Internet Is Not the Answer, Andrew Keen, a twenty-year veteran of the tech industry, traces the technological and economic history of the internet from its founding in the 1960s through the rise of the big data companies to the increasing attempts to monetize almost every human activity, and investigates how the internet is reconfiguring our world—often at great cost. In this sharp, witty narrative, informed by the work of other writers, academics, and reporters, as well as his own wide-ranging research and interviews, Keen shows us the tech world, warts and all, and investigates what we can do to make sure the choices we make about the reconfiguring of our society do not lead to unpleasant unforeseen aftershocks.

    It has been expanded and improved with: - Easy ways to create "read alike" lists, identifying what else is "like" a favorite book- Practical guidelines for conducting the advisory interview so it's a comfortable exchange- Confidence-boosting tactics for drawing on reviews to make recommendations- Methods for incorporating nonfiction into the discussion- More resources and online tools

    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!

    Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge.Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data- including stream data, sequence data, graph structured data, social network data, and multi-relational data.A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business dataUpdates that incorporate input from readers, changes in the field, and more material on statistics and machine learningDozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projectsComplete classroom support for instructors at www.mkp.com/datamining2e companion site

    Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges.It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.

    Acclaimed data scientist DJ Patil details a new approach to solving problems in Data Jujitsu.Learn how to use a problem's "weight" against itself to:Break down seemingly complex data problems into simplified partsUse alternative data analysis techniques to examine themUse human input, such as Mechanical Turk, and design tricks that enlist the help of your users to take short cuts around tough problemsLearn more about the problems before starting on the solutions—and use the findings to solve them, or determine whether the problems are worth solving at all.

    Social networks surrender their original missions to more immediately profitable data mining, while brokerage houses abandon value investing for algorithms that drain markets and our 401ks alike--all tactics driven by the need to stoke growth by any means necessary. Instead of taking this opportunity to reprogram our economy for sustainability, we have doubled down on growth as its core command. We have reached the limits of this approach. We must escape the growth trap, once and for all. Media scholar and technology author Douglas Rushkoff--one of today's most original and influential thinkers--argues for a new economic program that utilizes the unique distributive power of the internet while breaking free of the winner-take-all system the growth trap leaves in its wake. Drawing on sources both contemporary and historical, Rushkoff pioneers a new understanding of the old economic paradigm, from central currency to debt to corporations and labor.Most importantly, he offers a series of practical steps for businesses, consumers, investors, and policymakers to remake the economic operating system from the inside out--and prosper along the way. Instead of boycotting Wal-Mart or overtaxing the wealthy, we simply implement strategies that foster the creation of value by stakeholders other than just ourselves. From our currency to our labor to the corporation, every aspect of the economy can be reprogrammed with minimal disruption to create a more equitably distributed prosperity for all.Inspiring and challenging, Throwing Rocks at the Google Bus provides a pragmatic, optimistic, and human-centered model for economic progress in the digital age.

    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.

    The Art of Relevance is your guide to mattering more to more people. You'll find inspiring examples, rags-to-relevance case studies, research-based frameworks, and practical advice on how your work can be more vital to your community. Whether you work in museums or libraries, parks or theaters, churches or afterschool programs, relevance can work for you. Break through shallow connection. Unlock meaning for yourself and others. Find true relevance and shine.

    This comprehensive work covers both statistical and symbolic approaches to language processing; it shows how they can be applied to important tasks such as speech recognition, spelling and grammar correction, information extraction, search engines, machine translation, and the creation of spoken-language dialog agents. The following distinguishing features make the text both an introduction to the field and an advanced reference guide.- UNIFIED AND COMPREHENSIVE COVERAGE OF THE FIELDCovers the fundamental algorithms of each field, whether proposed for spoken or written language, whether logical or statistical in origin.- EMPHASIS ON WEB AND OTHER PRACTICAL APPLICATIONSGives readers an understanding of how language-related algorithms can be applied to important real-world problems.- EMPHASIS ON SCIENTIFIC EVALUATIONOffers a description of how systems are evaluated with each problem domain.- EMPERICIST/STATISTICAL/MACHINE LEARNING APPROACHES TO LANGUAGE PROCESSINGCovers all the new statistical approaches, while still completely covering the earlier more structured and rule-based methods.

    That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics—we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us.” If we can toss aside our fears and learn to approach them clearly—understanding how our own preconceptions lead us astray—statistics can point to ways we can live better and work smarter.As “perhaps the best popular economics writer in the world” (New Statesman), Tim Harford is an expert at taking complicated ideas and untangling them for millions of readers. In The Data Detective, he uses new research in science and psychology to set out ten strategies for using statistics to erase our biases and replace them with new ideas that use virtues like patience, curiosity, and good sense to better understand ourselves and the world. As a result, The Data Detective is a big-idea book about statistics and human behavior that is fresh, unexpected, and insightful.

    In this new book, Wurman examines how the Internet, desktop computing, and advances in digital technology have not simply enhanced access to information, but in fact have changed the way we live and work. In examining the sources of information anxiety, Wurman takes an in-depth look at how technological advances can hinder understanding and influence how business is conducted.

    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.