It is one of the fastest growing companies in history, an essential part of the social life not only of teenagers but hundreds of millions of adults worldwide. As Facebook spreads around the globe, it creates surprising effects—even becoming instrumental in political protests from Colombia to Iran. Veteran technology reporter David Kirkpatrick had the full cooperation of Facebook’s key executives in researching this fascinating history of the company and its impact on our lives. Kirkpatrick tells us how Facebook was created, why it has flourished, and where it is going next. He chronicles its successes and missteps, and gives readers the most complete assessment anywhere of founder and CEO Mark Zuckerberg, the central figure in the company’s remarkable ascent. This is the Facebook story that can be found nowhere else. How did a nineteen-year-old Harvard student create a company that has transformed the Internet and how did he grow it to its current enormous size? Kirkpatrick shows how Zuckerberg steadfastly refused to compromise his vision, insistently focusing on growth over profits and preaching that Facebook must dominate (his word) communication on the Internet. In the process, he and a small group of key executives have created a company that has changed social life in the United States and elsewhere, a company that has become a ubiquitous presence in marketing, altering politics, business, and even our sense of our own identity. This is the Facebook Effect.

    It used to be that to diagnose an illness, interpret legal documents, analyze foreign policy, or write a newspaper article you needed a human being with specific skills—and maybe an advanced degree or two. These days, high-level tasks are increasingly being handled by algorithms that can do precise work not only with speed but also with nuance. These “bots” started with human programming and logic, but now their reach extends beyond what their creators ever expected. In this fascinating, frightening book, Christopher Steiner tells the story of how algorithms took over—and shows why the “bot revolution” is about to spill into every aspect of our lives, often silently, without our knowledge. The May 2010 “Flash Crash” exposed Wall Street’s reliance on trading bots to the tune of a 998-point market drop and $1 trillion in vanished market value. But that was just the beginning. In Automate This, we meet bots that are driving cars, penning haiku, and writing music mistaken for Bach’s. They listen in on our customer service calls and figure out what Iran would do in the event of a nuclear standoff. There are algorithms that can pick out the most cohesive crew of astronauts for a space mission or identify the next Jeremy Lin. Some can even ingest statistics from baseball games and spit out pitch-perfect sports journalism indistinguishable from that produced by humans. The interaction of man and machine can make our lives easier. But what will the world look like when algorithms control our hospitals, our roads, our culture, and our national security? What hap­pens to businesses when we automate judgment and eliminate human instinct? And what role will be left for doctors, lawyers, writers, truck drivers, and many others?  Who knows—maybe there’s a bot learning to do your job this minute.

    Those engaged in business analysis are charged with identifying the activities that enable the company to define the business problem or opportunity, define what the solutions looks like, and define how it should behave in the end. As a BA, you lay out the plans for the process ahead."Business Analysis For Dummies" is the go to reference on how to make the complex topic of business analysis easy to understand. Whether you are new or have experience with business analysis, this book gives you the tools, techniques, tips and tricks to set your project's expectations and on the path to success.Offers guidance on how to make an impact in your organization by performing business analysisShows you the tools and techniques to be an effective business analysis professionalProvides a number of examples on how to perform business analysis regardless of your roleIf you're interested in learning about the tools and techniques used by successful business analysis professionals, "Business Analysis For Dummies" has you covered.

    R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you'll need to accomplish 80 percent of modern data tasks. Lander's self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You'll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you'll construct several complete models, both linear and nonlinear, and use some data mining techniques. By the time you're done, you won't just know how to write R programs, you'll be ready to tackle the statistical problems you care about most. COVERAGE INCLUDES - Exploring R, RStudio, and R packages - Using R for math: variable types, vectors, calling functions, and more - Exploiting data structures, including data.frames, matrices, and lists - Creating attractive, intuitive statistical graphics - Writing user-defined functions - Controlling program flow with if, ifelse, and complex checks - Improving program efficiency with group manipulations - Combining and reshaping multiple datasets - Manipulating strings using R's facilities and regular expressions - Creating normal, binomial, and Poisson probability distributions - Programming basic statistics: mean, standard deviation, and t-tests - Building linear, generalized linear, and nonlinear models - Assessing the quality of models and variable selection - Preventing overfitting, using the Elastic Net and Bayesian methods - Analyzing univariate and multivariate time series data - Grouping data via K-means and hierarchical clustering - Preparing reports, slideshows, and web pages with knitr - Building reusable R packages with devtools and Rcpp - Getting involved with the R global community

    Corporations & government agencies around the world are pouring billions into achieving AI’s Holy Grail—human-level intelligence. Once AI has attained it, scientists argue, it will have survival drives much like our own. We may be forced to compete with a rival more cunning, more powerful & more alien than we can imagine. Thru profiles of tech visionaries, industry watchdogs & groundbreaking AI systems, James Barrat's Our Final Invention explores the perils of the heedless pursuit of advanced AI. Until now, human intelligence has had no rival. Can we coexist with beings whose intelligence dwarfs our own? Will they allow us to?

    Politicians and marketers present shoddy evidence for dubious claims all the time. But smart people make mistakes too, and when it comes to statistics, plenty of otherwise great scientists--yes, even those published in peer-reviewed journals--are doing statistics wrong."Statistics Done Wrong" comes to the rescue with cautionary tales of all-too-common statistical fallacies. It'll help you see where and why researchers often go wrong and teach you the best practices for avoiding their mistakes.In this book, you'll learn: - Why "statistically significant" doesn't necessarily imply practical significance- Ideas behind hypothesis testing and regression analysis, and common misinterpretations of those ideas- How and how not to ask questions, design experiments, and work with data- Why many studies have too little data to detect what they're looking for-and, surprisingly, why this means published results are often overestimates- Why false positives are much more common than "significant at the 5% level" would suggestBy walking through colorful examples of statistics gone awry, the book offers approachable lessons on proper methodology, and each chapter ends with pro tips for practicing scientists and statisticians. No matter what your level of experience, "Statistics Done Wrong" will teach you how to be a better analyst, data scientist, or researcher.

    This practical introduction illuminates new features and capabilities, with scenarios demonstrating how the platform can meet the needs of your business.Based on beta software, this book provides the early, high-level information you need to begin preparing now for deployment and management. Topics include:Virtualization and cloud solutions Availability Provisioning and storage management Security and scalability Infrastructure options Server administration

    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.

    They are typically used to categorize something based on other data that you have. The purpose of this book is to help you understand how Random Forests work, as well as the different options that you have when using them to analyze a problem. Additionally, since Decision Trees are a fundamental part of Random Forests, this book explains how they work. This book is focused on understanding Random Forests at the conceptual level. Knowing how they work, why they work the way that they do, and what options are available to improve results. This book covers how Random Forests work in an intuitive way, and also explains the equations behind many of the functions, but it only has a small amount of actual code (in python). This book is focused on giving examples and providing analogies for the most fundamental aspects of how random forests and decision trees work. The reason is that those are easy to understand and they stick with you. There are also some really interesting aspects of random forests, such as information gain, feature importances, or out of bag error, that simply cannot be well covered without diving into the equations of how they work. For those the focus is providing the information in a straight forward and easy to understand way.

    From creating new data-driven products through to increasing operational efficiency, big data has the potential to makeyour organization both more competitive and more innovative.As this emerging field transitions from the bleeding edge to enterprise infrastructure, it's vital to understand not only the technologies involved, but the organizational and cultural demands of being data-driven.Written by O'Reilly Radar's experts on big data, this anthology describes:- The broad industry changes heralded by the big data era- What big data is, what it means to your business, and how to start solving data problems- The software that makes up the Hadoop big data stack, and the major enterprise vendors' Hadoop solutions- The landscape of NoSQL databases and their relative merits- How visualization plays an important part in data work

    As a result, many people are left with an incomplete understanding of this transformative new technology and its massive implications for the future. The goal of this book is not to plumb the depths of the mathematical wizardry used to code blockchain-based applications, but rather to serve as an introduction to the broader architecture and conceptual background behind blockchain technology. We will take a practical approach, examining how Blockchains are used in the real world. In this short, concise guide you will learn: A Brief History of Blockchain Technology Blockchain Basics: Managing Digital Transactions What is a Distributed Ledger? Blockchain Beyond Bitcoin Implications Of Blockchain: Big Data, Privacy & Personal Data Profiting from Blockchain Technologies Limitations & Challenges of Blockchain The Future of Blockchain For Centuries, people have relied on corrupt Centralized Institutions like banks and Governments to serve as intermediaries when it comes to storing and transacting financial assets. This is ALL About To Change... Make sure you take action and join the Financial Revolution by reading this book!

    It's not just a technical book or just a businessguide. Data is ubiquitous and it doesn't pay much attention toborders, so we've calibrated our coverage to follow it wherever itgoes.In the first edition of Big Data Now, the O'Reilly team tracked thebirth and early development of data tools and data science. Now, withthis second edition, we're seeing what happens when big data grows up:how it's being applied, where it's playing a role, and theconsequences -- good and bad alike -- of data's ascendance.We've organized the second edition of Big Data Now into five areas:Getting Up to Speed With Big Data -- Essential information on thestructures and definitions of big data.Big Data Tools, Techniques, and Strategies -- Expert guidance forturning big data theories into big data products.The Application of Big Data -- Examples of big data in action,including a look at the downside of data.What to Watch for in Big Data -- Thoughts on how big data will evolveand the role it will play across industries and domains.Big Data and Health Care -- A special section exploring thepossibilities that arise when data and health care come together.

    “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

    Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts’ predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight, and Tetlock has spent the past decade trying to figure out why. What makes some people so good? And can this talent be taught?   In Superforecasting, Tetlock and coauthor Dan Gardner offer a masterwork on prediction, drawing on decades of research and the results of a massive, government-funded forecasting tournament. The Good Judgment Project involves tens of thousands of ordinary people—including a Brooklyn filmmaker, a retired pipe installer, and a former ballroom dancer—who set out to forecast global events. Some of the volunteers have turned out to be astonishingly good. They’ve beaten other benchmarks, competitors, and prediction markets. They’ve even beaten the collective judgment of intelligence analysts with access to classified information. They are "superforecasters."   In this groundbreaking and accessible book, Tetlock and Gardner show us how we can learn from this elite group. Weaving together stories of forecasting successes (the raid on Osama bin Laden’s compound) and failures (the Bay of Pigs) and interviews with a range of high-level decision makers, from David Petraeus to Robert Rubin, they show that good forecasting doesn’t require powerful computers or arcane methods. It involves gathering evidence from a variety of sources, thinking probabilistically, working in teams, keeping score, and being willing to admit error and change course. Superforecasting offers the first demonstrably effective way to improve our ability to predict the future—whether in business, finance, politics, international affairs, or daily life—and is destined to become a modern classic.

    They report to the board on the health of their workforce, their financials, their customers, and their partnerships, but rarely the health of their information assets. Corporations typically exhibit greater discipline in tracking and accounting for their office furniture than their data. Infonomics is the theory, study, and discipline of asserting economic significance to information. It strives to apply both economic and asset management principles and practices to the valuation, handling, and deployment of information assets. This book specifically shows: CEOs and business leaders how to more fully wield information as a corporate asset CIOs how to improve the flow and accessibility of information CFOs how to help their organizations measure the actual and latent value in their information assets. More directly, this book is for the burgeoning force of chief data officers (CDOs) and other information and analytics leaders in their valiant struggle to help their organizations become more infosavvy. Author Douglas Laney has spent years researching and developing Infonomics and advising organizations on the infinite opportunities to monetize, manage, and measure information. This book delivers a set of new ideas, frameworks, evidence, and even approaches adapted from other disciplines on how to administer, wield, and understand the value of information. Infonomics can help organizations not only to better develop, sell, and market their offerings, but to transform their organizations altogether.