Everybody Lies

Everybody Lies Author Seth Stephens-Davidowitz
ISBN-10 9780062390875
Year 2017-05-09
Pages 354
Language en
Publisher HarperCollins
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Foreword by Steven Pinker Blending the informed analysis of The Signal and the Noise with the instructive iconoclasm of Think Like a Freak, a fascinating, illuminating, and witty look at what the vast amounts of information now instantly available to us reveals about ourselves and our world—provided we ask the right questions. By the end of an average day in the early twenty-first century, human beings searching the internet will amass eight trillion gigabytes of data. This staggering amount of information—unprecedented in history—can tell us a great deal about who we are—the fears, desires, and behaviors that drive us, and the conscious and unconscious decisions we make. From the profound to the mundane, we can gain astonishing knowledge about the human psyche that less than twenty years ago, seemed unfathomable. Everybody Lies offers fascinating, surprising, and sometimes laugh-out-loud insights into everything from economics to ethics to sports to race to sex, gender and more, all drawn from the world of big data. What percentage of white voters didn’t vote for Barack Obama because he’s black? Does where you go to school effect how successful you are in life? Do parents secretly favor boy children over girls? Do violent films affect the crime rate? Can you beat the stock market? How regularly do we lie about our sex lives and who’s more self-conscious about sex, men or women? Investigating these questions and a host of others, Seth Stephens-Davidowitz offers revelations that can help us understand ourselves and our lives better. Drawing on studies and experiments on how we really live and think, he demonstrates in fascinating and often funny ways the extent to which all the world is indeed a lab. With conclusions ranging from strange-but-true to thought-provoking to disturbing, he explores the power of this digital truth serum and its deeper potential—revealing biases deeply embedded within us, information we can use to change our culture, and the questions we’re afraid to ask that might be essential to our health—both emotional and physical. All of us are touched by big data everyday, and its influence is multiplying. Everybody Lies challenges us to think differently about how we see it and the world.

We Are Data

We Are Data Author John Cheney-Lippold
ISBN-10 9781479857593
Year 2017-05-02
Pages 320
Language en
Publisher NYU Press
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What identity means in an algorithmic age: how it works, how our lives are controlled by it, and how we can resist it Algorithms are everywhere, organizing the near limitless data that exists in our world. Derived from our every search, like, click, and purchase, algorithms determine the news we get, the ads we see, the information accessible to us and even who our friends are. These complex configurations not only form knowledge and social relationships in the digital and physical world, but also determine who we are and who we can be, both on and offline. Algorithms create and recreate us, using our data to assign and reassign our gender, race, sexuality, and citizenship status. They can recognize us as celebrities or mark us as terrorists. In this era of ubiquitous surveillance, contemporary data collection entails more than gathering information about us. Entities like Google, Facebook, and the NSA also decide what that information means, constructing our worlds and the identities we inhabit in the process. We have little control over who we algorithmically are. Our identities are made useful not for us—but for someone else. Through a series of entertaining and engaging examples, John Cheney-Lippold draws on the social constructions of identity to advance a new understanding of our algorithmic identities. We Are Data will educate and inspire readers who want to wrest back some freedom in our increasingly surveilled and algorithmically-constructed world.

Internet of Things and Data Analytics Handbook

Internet of Things and Data Analytics Handbook Author Hwaiyu Geng
ISBN-10 9781119173649
Year 2017-01-10
Pages 800
Language en
Publisher John Wiley & Sons
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This book examines the Internet of Things (IoT) and Data Analytics from a technical, application, and business point of view. Internet of Things and Data Analytics Handbook describes essential technical knowledge, building blocks, processes, design principles, implementation, and marketing for IoT projects. It provides readers with knowledge in planning, designing, and implementing IoT projects. The book is written by experts on the subject matter, including international experts from nine countries in the consumer and enterprise fields of IoT. The text starts with an overview and anatomy of IoT, ecosystem of IoT, communication protocols, networking, and available hardware, both present and future applications and transformations, and business models. The text also addresses big data analytics, machine learning, cloud computing, and consideration of sustainability that are essential to be both socially responsible and successful. Design and implementation processes are illustrated with best practices and case studies in action. In addition, the book: Examines cloud computing, data analytics, and sustainability and how they relate to IoT overs the scope of consumer, government, and enterprise applications Includes best practices, business model, and real-world case studies Hwaiyu Geng, P.E., is a consultant with Amica Research (www.AmicaResearch.org, Palo Alto, California), promoting green planning, design, and construction projects. He has had over 40 years of manufacturing and management experience, working with Westinghouse, Applied Materials, Hewlett Packard, and Intel on multi-million high-tech projects. He has written and presented numerous technical papers at international conferences. Mr. Geng, a patent holder, is also the editor/author of Data Center Handbook (Wiley, 2015).

The Internet of Us Knowing More and Understanding Less in the Age of Big Data

The Internet of Us  Knowing More and Understanding Less in the Age of Big Data Author Michael P. Lynch
ISBN-10 9781631491863
Year 2016-03-21
Pages 288
Language en
Publisher W. W. Norton & Company
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With far-reaching implications, this urgent treatise promises to revolutionize our understanding of what it means to be human in the digital age. We used to say "seeing is believing"; now googling is believing. With 24/7 access to nearly all of the world's information at our fingertips, we no longer trek to the library or the encyclopedia shelf in search of answers. We just open our browsers, type in a few keywords and wait for the information to come to us. Indeed, the Internet has revolutionized the way we learn and know, as well as how we interact with each other. And yet this explosion of technological innovation has also produced a curious paradox: even as we know more, we seem to understand less. While a wealth of literature has been devoted to life with the Internet, the deep philosophical implications of this seismic shift have not been properly explored until now. Demonstrating that knowledge based on reason plays an essential role in society and that there is much more to “knowing” than just acquiring information, leading philosopher Michael Patrick Lynch shows how our digital way of life makes us overvalue some ways of processing information over others, and thus risks distorting what it means to be human. With far-reaching implications, Lynch's argument charts a path from Plato's cave to Shannon's mathematical theory of information to Google Glass, illustrating that technology itself isn't the problem, nor is it the solution. Instead, it will be the way in which we adapt our minds to these new tools that will ultimately decide whether or not the "Internet of Things"—all those gadgets on our wrists, in our pockets and on our laps—will be a net gain for humanity. Along the way, Lynch uses a philosopher's lens to examine some of the most urgent issues facing digital life today, including how social media is revolutionizing the way we think about privacy; why a greater reliance on Wikipedia and Google doesn't necessarily make knowledge "more democratic"; and the perils of using "big data" alone to predict cultural trends. Promising to modernize our understanding of what it means to be human in the digital age, The Internet of Us builds on previous works by Nicholas Carr, James Gleick and Jaron Lanier to give us a necessary guide on how to navigate the philosophical quagmire that is the Information Age.

Uncharted

Uncharted Author Erez Aiden
ISBN-10 9781101632116
Year 2013-12-26
Pages 288
Language en
Publisher Penguin
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“One of the most exciting developments from the world of ideas in decades, presented with panache by two frighteningly brilliant, endearingly unpretentious, and endlessly creative young scientists.” – Steven Pinker, author of The Better Angels of Our Nature Our society has gone from writing snippets of information by hand to generating a vast flood of 1s and 0s that record almost every aspect of our lives: who we know, what we do, where we go, what we buy, and who we love. This year, the world will generate 5 zettabytes of data. (That’s a five with twenty-one zeros after it.) Big data is revolutionizing the sciences, transforming the humanities, and renegotiating the boundary between industry and the ivory tower. What is emerging is a new way of understanding our world, our past, and possibly, our future. In Uncharted, Erez Aiden and Jean-Baptiste Michel tell the story of how they tapped into this sea of information to create a new kind of telescope: a tool that, instead of uncovering the motions of distant stars, charts trends in human history across the centuries. By teaming up with Google, they were able to analyze the text of millions of books. The result was a new field of research and a scientific tool, the Google Ngram Viewer, so groundbreaking that its public release made the front page of The New York Times, The Wall Street Journal, and The Boston Globe, and so addictive that Mother Jones called it “the greatest timewaster in the history of the internet.” Using this scope, Aiden and Michel—and millions of users worldwide—are beginning to see answers to a dizzying array of once intractable questions. How quickly does technology spread? Do we talk less about God today? When did people start “having sex” instead of “making love”? At what age do the most famous people become famous? How fast does grammar change? Which writers had their works most effectively censored by the Nazis? When did the spelling “donut” start replacing the venerable “doughnut”? Can we predict the future of human history? Who is better known—Bill Clinton or the rutabaga? All over the world, new scopes are popping up, using big data to quantify the human experience at the grandest scales possible. Yet dangers lurk in this ocean of 1s and 0s—threats to privacy and the specter of ubiquitous government surveillance. Aiden and Michel take readers on a voyage through these uncharted waters.

Big Data

Big Data Author Viktor Mayer-Schönberger
ISBN-10 9780544002937
Year 2013-03-05
Pages 240
Language en
Publisher Houghton Mifflin Harcourt
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A revelatory exploration of the hottest trend in technology and the dramatic impact it will have on the economy, science, and society at large. Which paint color is most likely to tell you that a used car is in good shape? How can officials identify the most dangerous New York City manholes before they explode? And how did Google searches predict the spread of the H1N1 flu outbreak? The key to answering these questions, and many more, is big data. “Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior. In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing. www.big-data-book.com

The End of Theory

The End of Theory Author Richard Bookstaber
ISBN-10 9781400884964
Year 2017-04-17
Pages 240
Language en
Publisher Princeton University Press
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An in-depth look at how to account for the human complexities at the heart of today's financial system Our economy may have recovered from the Great Recession—but not our economics. In The End of Theory, Richard Bookstaber discusses why the human condition and the radical uncertainty of our world renders the standard economic model—and the theory behind it—useless for dealing with financial crises. What model should replace it? None. At least not any version we've been using for the past two hundred years. Instead, Bookstaber argues for a new approach called agent-based economics, one that takes as a starting point the fact that we are humans, not the optimizing automatons that standard economics assumes we are. Bookstaber's groundbreaking paradigm promises to do a far better job at preventing crises and managing those that break out. As he explains, our varied memories and imaginations color our economic behavior in unexpected hues. Agent-based modeling embraces these nuances by avoiding the mechanistic, unrealistic structure of our current economic approach. Bookstaber tackles issues such as radical uncertainty, when circumstances take place beyond our anticipation, and emergence, when innocent, everyday interactions combine to create sudden chaos. Starting with the realization that future crises cannot be predicted by the past, he proposes an approach that recognizes the human narrative while addressing market realities. Sweeping aside the historic failure of twentieth-century economics, The End of Theory offers a novel and innovative perspective, along with a more realistic and human framework, to help prevent today's financial system from blowing up again.

Weapons of Math Destruction

Weapons of Math Destruction Author Cathy O'Neil
ISBN-10 9780553418828
Year 2016-09-06
Pages 272
Language en
Publisher Crown
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Longlisted for the National Book Award New York Times Bestseller A former Wall Street quant sounds an alarm on the mathematical models that pervade modern life — and threaten to rip apart our social fabric We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we get a car loan, how much we pay for health insurance—are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated. But as Cathy O’Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they’re wrong. Most troubling, they reinforce discrimination: If a poor student can’t get a loan because a lending model deems him too risky (by virtue of his zip code), he’s then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a “toxic cocktail for democracy.” Welcome to the dark side of Big Data. Tracing the arc of a person’s life, O’Neil exposes the black box models that shape our future, both as individuals and as a society. These “weapons of math destruction” score teachers and students, sort résumés, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health. O’Neil calls on modelers to take more responsibility for their algorithms and on policy makers to regulate their use. But in the end, it’s up to us to become more savvy about the models that govern our lives. This important book empowers us to ask the tough questions, uncover the truth, and demand change. — Longlist for National Book Award (Non-Fiction) — Goodreads, semi-finalist for the 2016 Goodreads Choice Awards (Science and Technology) — Kirkus, Best Books of 2016 — New York Times, 100 Notable Books of 2016 (Non-Fiction) — The Guardian, Best Books of 2016 — WBUR's "On Point," Best Books of 2016: Staff Picks — Boston Globe, Best Books of 2016, Non-Fiction

Pale Rider

Pale Rider Author Laura Spinney
ISBN-10 9781473523920
Year 2017-06-01
Pages 352
Language en
Publisher Random House
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With a death toll of between 50 and 100 million people and a global reach, the Spanish flu of 1918–1920 was the greatest human disaster, not only of the twentieth century, but possibly in all of recorded history. And yet, in our popular conception it exists largely as a footnote to World War I. In Pale Rider, Laura Spinney recounts the story of an overlooked pandemic, tracing it from Alaska to Brazil, from Persia to Spain, and from South Africa to Odessa. Telling the story from the point of view of those who lived through it, she shows how the pandemic was shaped by the interaction of a virus and the humans it encountered; and how this devastating natural experiment put both the ingenuity and the vulnerability of humans to the test. Drawing on the latest research in history, virology, epidemiology, psychology, and economics, Laura Spinney narrates a catastrophe that changed humanity for decades to come, and continues to make itself felt today. In the process she demonstrates that the Spanish flu was as significant – if not more so – as two world wars in shaping the modern world; in disrupting, and often permanently altering, global politics, race relations, family structures, and thinking across medicine, religion and the arts.

Data Science Using Oracle Data Miner and Oracle R Enterprise

Data Science Using Oracle Data Miner and Oracle R Enterprise Author Sibanjan Das
ISBN-10 9781484226148
Year 2016-12-22
Pages 289
Language en
Publisher Apress
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Automate the predictive analytics process using Oracle Data Miner and Oracle R Enterprise. This book talks about how both these technologies can provide a framework for in-database predictive analytics. You'll see a unified architecture and embedded workflow to automate various analytics steps such as data preprocessing, model creation, and storing final model output to tables. You'll take a deep dive into various statistical models commonly used in businesses and how they can be automated for predictive analytics using various SQL, PLSQL, ORE, ODM, and native R packages. You'll get to know various options available in the ODM workflow for driving automation. Also, you'll get an understanding of various ways to integrate ODM packages, ORE, and native R packages using PLSQL for automating the processes. Data Science Automation Using Oracle Data Miner and Oracle R Enterprise starts with an introduction to business analytics, covering why automation is necessary and the level of complexity in automation at each analytic stage. Then, it focuses on how predictive analytics can be automated by using Oracle Data Miner and Oracle R Enterprise. Also, it explains when and why ODM and ORE are to be used together for automation. The subsequent chapters detail various statistical processes used for predictive analytics such as calculating attribute importance, clustering methods, regression analysis, classification techniques, ensemble models, and neural networks. In these chapters you will also get to understand the automation processes for each of these statistical processes using ODM and ORE along with their application in a real-life business use case. What you'll learn Discover the functionality of Oracle Data Miner and Oracle R Enterprise Gain methods to perform in-database predictive analytics Use Oracle's SQL and PLSQL APIs for building analytical solutions Acquire knowledge of common and widely-used business statistical analysis techniques Who this book is for IT executives, BI architects, Oracle architects and developers, R users and statisticians.

The Diversity Myth

The Diversity Myth Author David O. Sacks
ISBN-10 STANFORD:36105110324345
Year 1998
Pages 285
Language en
Publisher Independent Inst
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This is a powerful exploration of the debilitating impact that politically-correct “multiculturalism” has had upon higher education and academic freedom in the United States. In the name of diversity, many leading academic and cultural institutions are working to silence dissent and stifle intellectual life. This book exposes the real impact of multiculturalism on the institution most closely identified with the politically correct decline of higher education—Stanford University. Authored by two Stanford graduates, this book is a compelling insider’s tour of a world of speech codes, “dumbed-down” admissions standards and curricula, campus witch hunts, and anti-Western zealotry that masquerades as legitimate scholarly inquiry. Sacks and Thiel use numerous primary sources—the Stanford Daily, class readings, official university publications—to reveal a pattern of politicized classes, housing, budget priorities, and more. They trace the connections between such disparate trends as political correctness, the gender wars, Generation X nihilism, and culture wars, showing how these have played a role in shaping multiculturalism at institutions like Stanford. The authors convincingly show that multiculturalism is not about learning more; it is actually about learning less. They end their comprehensive study by detailing the changes necessary to reverse the tragic disintegration of American universities and restore true academic excellence.

The Outsiders

The Outsiders Author William N. Thorndike
ISBN-10 9781422187586
Year 2012-10-02
Pages 240
Language en
Publisher Harvard Business Press
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“An outstanding book about CEOs who excelled at capital allocation.” — Warren Buffett #1 on Warren Buffett’s Recommended Reading List, Berkshire Hathaway Annual Shareholder Letter, 2012 Named one of “19 Books Billionaire Charlie Munger Thinks You Should Read” in Business Insider. “A book that details the extraordinary success of CEOs who took a radically different approach to corporate management.” — Charlie Munger, Vice-Chairman of Berkshire Hathaway Corporation “Thorndike explores the importance of thoughtful capital allocation through the stories of eight successful CEOs. A good read for any business leader but especially those willing to chart their own course.” — Michael Dell, chairman of the board of directors and chief executive officer of Dell What makes a successful CEO? Most people call to mind a familiar definition: “a seasoned manager with deep industry expertise.” Others might point to the qualities of today’s so-called celebrity CEOs—charisma, virtuoso communication skills, and a confident management style. But what really matters when you run an organization? What is the hallmark of exceptional CEO performance? Quite simply, it is the returns for the shareholders of that company over the long term. In this refreshing, counterintuitive book, author Will Thorndike brings to bear the analytical wisdom of a successful career in investing, closely evaluating the performance of companies and their leaders. You will meet eight individualistic CEOs whose firms’ average returns outperformed the S&P 500 by a factor of twenty—in other words, an investment of $10,000 with each of these CEOs, on average, would have been worth over $1.5 million twenty-five years later. You may not know all their names, but you will recognize their companies: General Cinema, Ralston Purina, The Washington Post Company, Berkshire Hathaway, General Dynamics, Capital Cities Broadcasting, TCI, and Teledyne. In The Outsiders, you’ll learn the traits and methods—striking for their consistency and relentless rationality—that helped these unique leaders achieve such exceptional performance. Humble, unassuming, and often frugal, these “outsiders” shunned Wall Street and the press, and shied away from the hottest new management trends. Instead, they shared specific traits that put them and the companies they led on winning trajectories: a laser-sharp focus on per share value as opposed to earnings or sales growth; an exceptional talent for allocating capital and human resources; and the belief that cash flow, not reported earnings, determines a company’s long-term value. Drawing on years of research and experience, Thorndike tells eye-opening stories, extracting lessons and revealing a compelling alternative model for anyone interested in leading a company or investing in one—and reaping extraordinary returns.

Data Analytics with Hadoop

Data Analytics with Hadoop Author Benjamin Bengfort
ISBN-10 9781491913765
Year 2016-06-01
Pages 288
Language en
Publisher "O'Reilly Media, Inc."
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Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data. Understand core concepts behind Hadoop and cluster computing Use design patterns and parallel analytical algorithms to create distributed data analysis jobs Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase Use Sqoop and Apache Flume to ingest data from relational databases Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib