Now, in one of the greatest undertakings of the twenty-first century, a savvy group of mathematicians and computer scientists is beginning to sift through this data to dissect us and map out our next steps. Their goal? To manipulate our behavior -- what we buy, how we vote -- without our even realizing it.In this tour de force of original reporting and analysis, journalist Stephen Baker provides us with a fascinating guide to the world we're all entering -- and to the people controlling that world. The Numerati have infiltrated every realm of human affairs, profiling us as workers, shoppers, patients, voters, potential terrorists -- and lovers. The implications are vast. Our privacy evaporates. Our bosses can monitor and measure our every move (then reward or punish us). Politicians can find the swing voters among us, by plunking us all into new political groupings with names like "Hearth Keepers" and "Crossing Guards." It can sound scary. But the Numerati can also work on our behalf, diagnosing an illness before we're aware of the symptoms, or even helping us find our soul mate. Surprising, enlightening, and deeply relevant, The Numerati shows how a powerful new endeavor -- the mathematical modeling of humanity -- will transform every aspect of our lives. STEPHEN BAKER has written for BusinessWeek for over twenty years, covering Mexico and Latin America, the Rust Belt, European technology, and a host of other topics, including blogs, math, and nanotechnology. But he's always considered himself a foreign correspondent. This, he says, was especially useful as he met the Numerati. "While I came from the world of words, they inhabited the symbolic realms of math and computer science. This was foreign to me. My reporting became an anthropological mission." Baker has written for many publications, including the Wall Street Journal, the Los Angeles Times, and the Boston Globe. He won an Overseas Press Club Award for his portrait of the rising Mexican auto industry. He is the coauthor of blogspotting.net, featured by the New York Times as one of fifty blogs to watch.

    The data compiled and portraits created are incredibly detailed, to the point of being invasive. But who connects the dots about what firms are doing with this information? The Black Box Society argues that we all need to be able to do so--and to set limits on how big data affects our lives.Hidden algorithms can make (or ruin) reputations, decide the destiny of entrepreneurs, or even devastate an entire economy. Shrouded in secrecy and complexity, decisions at major Silicon Valley and Wall Street firms were long assumed to be neutral and technical. But leaks, whistleblowers, and legal disputes have shed new light on automated judgment. Self-serving and reckless behavior is surprisingly common, and easy to hide in code protected by legal and real secrecy. Even after billions of dollars of fines have been levied, underfunded regulators may have only scratched the surface of this troubling behavior.Frank Pasquale exposes how powerful interests abuse secrecy for profit and explains ways to rein them in. Demanding transparency is only the first step. An intelligible society would assure that key decisions of its most important firms are fair, nondiscriminatory, and open to criticism. Silicon Valley and Wall Street need to accept as much accountability as they impose on others.

    Whether you’re enraged by Ikea’s Verdanagate, want to know what the Beach Boys have in common with easy Jet or why it’s okay to like Comic Sans, Just My Type will have the answer. Learn why using upper case got a New Zealand health worker sacked. Refer to Prince in the Tafkap years as a Dingbat (that works on many levels). Spot where movies get their time periods wrong and don’t be duped by fake posters on eBay. Simon Garfield meets the people behind the typefaces and along the way learns why some fonts – like men – are from Mars and some are from Venus. From type on the high street and album covers, to the print in our homes and offices, Garfield is the font of all types of knowledge.

    Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud-computing technologies. This collection of essays expands on the vision of pioneering computer scientist Jim Gray for a new, fourth paradigm of discovery based on data-intensive science and offers insights into how it can be fully realized.

    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!

    This work represents the views of a mathematician on the analogies between computing machines and the living human brain.

    This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.

    In this lively and groundbreaking new book, economist Ian Ayres shows how today's best and brightest organizations are analyzing massive databases at lightening speed to provide greater insights into human behavior. They are the Super Crunchers. From internet sites like Google and Amazon that know your tastes better than you do, to a physician's diagnosis and your child's education, to boardrooms and government agencies, this new breed of decision makers are calling the shots. And they are delivering staggeringly accurate results. How can a football coach evaluate a player without ever seeing him play? Want to know whether the price of an airline ticket will go up or down before you buy? How can a formula outpredict wine experts in determining the best vintages? Super crunchers have the answers. In this brave new world of equation versus expertise, Ayres shows us the benefits and risks, who loses and who wins, and how super crunching can be used to help, not manipulate us.Gone are the days of solely relying on intuition to make decisions. No businessperson, consumer, or student who wants to stay ahead of the curve should make another keystroke without reading Super Crunchers.

    Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    Here is a complete library of dimensional modeling techniques-- the most comprehensive collection ever written. Greatly expanded to cover both basic and advanced techniques for optimizing data warehouse design, this second edition to Ralph Kimball's classic guide is more than sixty percent updated.The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including:* Retail sales and e-commerce* Inventory management* Procurement* Order management* Customer relationship management (CRM)* Human resources management* Accounting* Financial services* Telecommunications and utilities* Education* Transportation* Health care and insuranceBy the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.This book is also available as part of the Kimball's Data Warehouse Toolkit Classics Box Set (ISBN: 9780470479575) with the following 3 books:The Data Warehouse Toolkit, 2nd Edition (9780471200246)The Data Warehouse Lifecycle Toolkit, 2nd Edition (9780470149775)The Data Warehouse ETL Toolkit (9780764567575)

    These themes include mathematical reasoning, combinatorial analysis, discrete structures, algorithmic thinking, and enhanced problem-solving skills through modeling. Its intent is to demonstrate the relevance and practicality of discrete mathematics to all students. The Fifth Edition includes a more thorough and linear presentation of logic, proof types and proof writing, and mathematical reasoning. This enhanced coverage will provide students with a solid understanding of the material as it relates to their immediate field of study and other relevant subjects. The inclusion of applications and examples to key topics has been significantly addressed to add clarity to every subject. True to the Fourth Edition, the text-specific web site supplements the subject matter in meaningful ways, offering additional material for students and instructors. Discrete math is an active subject with new discoveries made every year. The continual growth and updates to the web site reflect the active nature of the topics being discussed. The book is appropriate for a one- or two-term introductory discrete mathematics course to be taken by students in a wide variety of majors, including computer science, mathematics, and engineering. College Algebra is the only explicit prerequisite.

    With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

    This book covers a range of genres, including action, adventure, and puzzle games complete with professional quality sound effects and visuals. It discusses game design theory and features practical examples of how this can be applied to making games that are more fun to play. Game Maker allows games to be created using a simple drag-and-drop interface, so you don't need to have any prior coding experience. It includes an optional programming language for adding advanced features to your games, when you feel ready to do so. You can obtain more information by visiting book.gamemaker.nl. The authors include the creator of the Game Maker tool and a former professional game programmer, so you'll glean understanding from their expertise. The book also includes a DVD containing Game Maker software and all of the game projects that are created in the book—plus a host of professional-quality graphics and sound effects that you can use in your own games.

    Users hold the crypto keys to their own money and transact directly with each other, with the help of a P2P network to check for double-spending.https://bitcoin.org/bitcoin.pdf