In Dataclysm, Christian Rudder uses it to show us who we truly are.   For centuries, we’ve relied on polling or small-scale lab experiments to study human behavior. Today, a new approach is possible. As we live more of our lives online, researchers can finally observe us directly, in vast numbers, and without filters. Data scientists have become the new demographers.   In this daring and original book, Rudder explains how Facebook "likes" can predict, with surprising accuracy, a person’s sexual orientation and even intelligence; how attractive women receive exponentially more interview requests; and why you must have haters to be hot. He charts the rise and fall of America’s most reviled word through Google Search and examines the new dynamics of collaborative rage on Twitter. He shows how people express themselves, both privately and publicly. What is the least Asian thing you can say? Do people bathe more in Vermont or New Jersey? What do black women think about Simon & Garfunkel? (Hint: they don’t think about Simon & Garfunkel.) Rudder also traces human migration over time, showing how groups of people move from certain small towns to the same big cities across the globe. And he grapples with the challenge of maintaining privacy in a world where these explorations are possible.   Visually arresting and full of wit and insight, Dataclysm is a new way of seeing ourselves—a brilliant alchemy, in which math is made human and numbers become the narrative of our time.

    Stay in the know, spot trends as they happen, and push your business to new limits. This e-book introduces Microsoft Power BI basics through a practical, scenario-based guided tour of the tool, showing you how to build analytical solutions using Power BI. Get an overview of Power BI, or dig deeper and follow along on your PC using the book's examples.

    This book covers it all! Encrypting your private files, securing your PC, masking your online footsteps, and all while giving you peace of mind with TOTAL 100% ANONYMITY. Don't waste months scouring the internet for info. Just read this! You'll be hooked in five minutes. It's all here: CIA techniques, how the NSA catches Tor users, Truecrypt and the FBI, nuking tracking cookies, private browsing, preventing identity theft. I will show you: -How to Be Anonymous Online -Step by Step Guides for Tor, Freenet, I2P, VPNs, Usenet and more -Browser Fingerprinting -Anti-Hacking and Counter-Forensic Techniques -Photo & Video Metadata -How to Encrypt Files (I make this super simple) -How to Defeat NSA Spying -How to Browse the Deep Web -How to Protect Your Identity -How to Hide Anything! You've probably read How to Be Invisible by J. J. Luna and Incognito Toolkit by Rob Robideau, and while they are fine books, you need this companion piece to take it to the next level!

    

    But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that.This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples.By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to:- How to measure your own level of uncertainty in a conclusion or belief- Calculate Bayes theorem and understand what it's useful for- Find the posterior, likelihood, and prior to check the accuracy of your conclusions- Calculate distributions to see the range of your data- Compare hypotheses and draw reliable conclusions from themNext time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.

    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!

    The results of Artificial Intelligence have been invaluable to biologists, psychologists, and linguists in helping tounderstand the processes of memory, learning, and language from a fresh angle.As a concept, Artificial Intelligence has fueled and sharpened the philosophical debates concerning the nature of the mind, intelligence, and the uniqueness of human beings. In this Very Short Introduction, Margaret A. Boden reviews the philosophical and technological challenges raised by ArtificialIntelligence, considering whether programs could ever be really intelligent, creative, or even conscious, and shows how the pursuit of Artificial Intelligence has helped us to appreciate how human and animal minds are possible.ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, andenthusiasm to make interesting and challenging topics highly readable.

    China delivered a bold message when it released a national plan to dominate all aspects of AI across the planet. Within weeks, Russia's Vladimir Putin raised the stakes by declaring AI the future for all humankind, and proclaiming that, "Whoever becomes the leader in this sphere will become the ruler of the world."The race was on. Consistent with their unique national agendas, countries throughout the world began plotting their paths and hurrying their pace. Now, not long after, the race has become a sprint.Despite everything at risk, for most of us AI remains shrouded by a cloud of mystery and misunderstanding. Hidden behind complex technical terms and confused even further by extravagant depictions in science fiction, the realities of AI and its profound implications are hard to decipher, but no less crucial to understand.In T-Minus AI: Humanity's Countdown to Artificial Intelligence and the New Pursuit of Global Power, author Michael Kanaan explains the realities of AI from a human-oriented perspective that's easy to comprehend. A recognized national expert and the U.S. Air Force's first Chairperson for Artificial Intelligence, Kanaan weaves a compelling new view on our history of innovation and technology to masterfully explain what each of us should know about modern computing, AI, and machine learning.Kanaan also illuminates the global implications of AI by highlighting the cultural and national vulnerabilities already exposed and the pressing issues now squarely on the table. AI has already become China's all-purpose tool to impose authoritarian influence around the world. Russia, playing catch up, is weaponizing AI through its military systems and now infamous, aggressive efforts to disrupt democracy by whatever disinformation means possible.America and like-minded nations are awakening to these new realities, and the paths they're electing to follow echo loudly, in most cases, the political foundations and moral imperatives upon which they were formed.As we march toward a future far different than ever imagined, T-Minus AI is fascinating and critically well-timed. It leaves the fiction behind, paints the alarming implications of AI for what they actually are, and calls for unified action to protect fundamental human rights and dignities for all.

    This groundbreaking and powerful theory now forms the basis of computer science. In Turing's Vision, Chris Bernhardt explains the theory, Turing's most important contribution, for the general reader. Bernhardt argues that the strength of Turing's theory is its simplicity, and that, explained in a straightforward manner, it is eminently understandable by the nonspecialist. As Marvin Minsky writes, -The sheer simplicity of the theory's foundation and extraordinary short path from this foundation to its logical and surprising conclusions give the theory a mathematical beauty that alone guarantees it a permanent place in computer theory.- Bernhardt begins with the foundation and systematically builds to the surprising conclusions. He also views Turing's theory in the context of mathematical history, other views of computation (including those of Alonzo Church), Turing's later work, and the birth of the modern computer.In the paper, -On Computable Numbers, with an Application to the Entscheidungsproblem, - Turing thinks carefully about how humans perform computation, breaking it down into a sequence of steps, and then constructs theoretical machines capable of performing each step. Turing wanted to show that there were problems that were beyond any computer's ability to solve; in particular, he wanted to find a decision problem that he could prove was undecidable. To explain Turing's ideas, Bernhardt examines three well-known decision problems to explore the concept of undecidability; investigates theoretical computing machines, including Turing machines; explains universal machines; and proves that certain problems are undecidable, including Turing's problem concerning computable numbers.

    You'll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.To get you started--whether you're on Windows, OS X, or Linux--author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.Discover why the command line is an agile, scalable, and extensible technology. Even if you're already comfortable processing data with, say, Python or R, you'll greatly improve your data science workflow by also leveraging the power of the command line.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on plain text, CSV, HTML/XML, and JSONExplore data, compute descriptive statistics, and create visualizationsManage your data science workflow using DrakeCreate reusable tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelines using GNU ParallelModel data with dimensionality reduction, clustering, regression, and classification algorithms

    Vivid photos capture these historically important machinesincluding the Eniac, Crays 13, Apple I and IIwhile authoritative text profiles each, telling the stories of their innovations and peculiarities. Thirty-five machines are profiled in over 100 extraordinary color photographs, making Core Memory a surprising addition to the library of photography collectors and the ultimate geek-chic gift.

    But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models—from linear regression to random walks and far beyond—that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.

    For centuries, such fears have been misplaced, and many economists maintain that they remain so today. But as Daniel Susskind demonstrates, this time really is different. Breakthroughs in artificial intelligence mean that all kinds of jobs are increasingly at risk.Drawing on almost a decade of research in the field, Susskind argues that machines no longer need to think like us in order to outperform us, as was once widely believed. As a result, more and more tasks that used to be far beyond the capability of computers – from diagnosing illnesses to drafting legal contracts, from writing news reports to composing music – are coming within their reach. The threat of technological unemployment is now real.This is not necessarily a bad thing, Susskind emphasizes. Technological progress could bring about unprecedented prosperity, solving one of humanity’s oldest problems: how to make sure that everyone has enough to live on. The challenges will be to distribute this prosperity fairly, to constrain the burgeoning power of Big Tech, and to provide meaning in a world where work is no longer the center of our lives. Perceptive, pragmatic, and ultimately hopeful, A World Without Work shows the way.

    Everything around us, including matter, is energy. A deep look into the mysteries of the subatomic world – the particles that make up the atom – provides answers to basic questions about how the universe works. To solve the future of mankind’s energy needs we need to understand the basic building blocks of the universe, including the atom and its parts. By exploring the subatomic world we’ll find more answers to our questions about time, forces like gravity and the matter that surrounds us. More importantly, we’ll find new ways to tap into the energy that exists around us to power our growing needs. In a new branch of particle physics, where tiny particles are thought of as energy waves, we find new answers that may help us in our quest to find alternative energy sources.

    By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.