Now, two science professors give us the tools to dismantle misinformation and think clearly in a world of fake news and bad data.It's increasingly difficult to know what's true. Misinformation, disinformation, and fake news abound. Our media environment has become hyperpartisan. Science is conducted by press release. Startup culture elevates bullshit to high art. We are fairly well equipped to spot the sort of old-school bullshit that is based in fancy rhetoric and weasel words, but most of us don't feel qualified to challenge the avalanche of new-school bullshit presented in the language of math, science, or statistics. In Calling Bullshit, Professors Carl Bergstrom and Jevin West give us a set of powerful tools to cut through the most intimidating data.You don't need a lot of technical expertise to call out problems with data. Are the numbers or results too good or too dramatic to be true? Is the claim comparing like with like? Is it confirming your personal bias? Drawing on a deep well of expertise in statistics and computational biology, Bergstrom and West exuberantly unpack examples of selection bias and muddled data visualization, distinguish between correlation and causation, and examine the susceptibility of science to modern bullshit.We have always needed people who call bullshit when necessary, whether within a circle of friends, a community of scholars, or the citizenry of a nation. Now that bullshit has evolved, we need to relearn the art of skepticism.

    His students, some of the nation’s brightest minds, were adrift when it came to the big questions: how to think critically and creatively, and how to find a sense of purpose.Excellent Sheep takes a sharp look at the high-pressure conveyor belt that begins with parents and counselors who demand perfect grades and culminates in the skewed applications Deresiewicz saw firsthand as a member of Yale’s admissions committee. As schools shift focus from the humanities to "practical" subjects like economics and computer science, students are losing the ability to think in innovative ways. Deresiewicz explains how college should be a time for self-discovery, when students can establish their own values and measures of success, so they can forge their own path. He addresses parents, students, educators, and anyone who's interested in the direction of American society, featuring quotes from real students and graduates he has corresponded with over the years, candidly exposing where the system is broken and clearly presenting solutions.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    The Google Story takes you deep inside the company's wild ride from an idea that struggled for funding in 1998 to a firm that rakes in billions in profits, making Brin and Page the wealthiest young men in America. Based on scrupulous research and extraordinary access to Google, this fast-moving narrative reveals how an unorthodox management style and culture of innovation enabled a search engine to shake up Madison Avenue and Wall Street, scoop up YouTube, and battle Microsoft at every turn. Not afraid of controversy, Google is expanding in Communist China and quietly working on a searchable genetic database, initiatives that test the founders' guiding mantra: DON'T BE EVIL.

    Thaler, and Cass R. Sunstein: a revelatory look at how we make decisionsNew York Times bestsellerNamed a Best Book of the Year by The Economist and the Financial Times Every day we make choices—about what to buy or eat, about financial investments or our children’s health and education, even about the causes we champion or the planet itself. Unfortunately, we often choose poorly. Nudge is about how we make these choices and how we can make better ones. Using dozens of eye-opening examples and drawing on decades of behavioral science research, Nobel Prize winner Richard H. Thaler and Harvard Law School professor Cass R. Sunstein show that no choice is ever presented to us in a neutral way, and that we are all susceptible to biases that can lead us to make bad decisions. But by knowing how people think, we can use sensible “choice architecture” to nudge people toward the best decisions for ourselves, our families, and our society, without restricting our freedom of choice.

    In this one-of-a-kind account, you'll see how the developers responsible for these flaws patched the bugs—or failed to respond at all. As you follow Klein on his journey, you'll gain deep technical knowledge and insight into how hackers approach difficult problems and experience the true joys (and frustrations) of bug hunting.Along the way you'll learn how to:Use field-tested techniques to find bugs, like identifying and tracing user input data and reverse engineering Exploit vulnerabilities like NULL pointer dereferences, buffer overflows, and type conversion flaws Develop proof of concept code that verifies the security flaw Report bugs to vendors or third party brokersA Bug Hunter's Diary is packed with real-world examples of vulnerable code and the custom programs used to find and test bugs. Whether you're hunting bugs for fun, for profit, or to make the world a safer place, you'll learn valuable new skills by looking over the shoulder of a professional bug hunter in action.

    The book is broken into two parts, the first deals with security-related reverse engineering and the second explores the more practical aspects of reverse engineering. In addition, the author explains how to reverse engineer a third-party software library to improve interfacing and how to reverse engineer a competitor's software to build a better product. * The first popular book to show how software reverse engineering can help defend against security threats, speed up development, and unlock the secrets of competitive products * Helps developers plug security holes by demonstrating how hackers exploit reverse engineering techniques to crack copy-protection schemes and identify software targets for viruses and other malware * Offers a primer on advanced reverse-engineering, delving into disassembly-code-level reverse engineering-and explaining how to decipher assembly language

    What you'll find here is practical magic: unique knowledge, drawn from a variety of sciences, revealing what charisma really is and how it works. You'll get both the insights and the techniques you need to apply this knowledge. The world will become your lab, and every person you meet, a chance to experiment.The Charisma Myth is a mix of fun stories, sound science, and practical tools. Cabane takes a hard scientific approach to a heretofore mystical topic, covering what charisma actually is, how it is learned, what its side effects are, and how to handle them.

    With this hands-on guide, you'll learn how to write effective, idiomatic Python code by leveraging its best and possibly most neglected features. Author Luciano Ramalho takes you through Python's core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time.Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.This book covers:Python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritanceControl flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packagesMetaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work"

    Did you design your system to survivef a sudden rush of visitors from Digg or Slashdot? Or an influx of real world customers from 100 different countries? Are you ready for a world filled with flakey networks, tangled databases, and impatient users?If you're a developer and don't want to be on call for 3AM for the rest of your life, this book will help.In Release It!, Michael T. Nygard shows you how to design and architect your application for the harsh realities it will face. You'll learn how to design your application for maximum uptime, performance, and return on investment.Mike explains that many problems with systems today start with the design.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    One of the greatest partnerships in the history of science, Kahneman and Tversky’s extraordinary friendship incited a revolution in Big Data studies, advanced evidence-based medicine, led to a new approach to government regulation, and made much of Michael Lewis’s own work possible. In The Undoing Project, Lewis shows how their Nobel Prize–winning theory of the mind altered our perception of reality.

    Rather, other factors can be even more crucial such as identifying our passions and following through on our commitments.Drawing on her own powerful story as the daughter of a scientist who frequently bemoaned her lack of smarts, Duckworth describes her winding path through teaching, business consulting, and neuroscience, which led to the hypothesis that what really drives success is not genius, but a special blend of passion and long-term perseverance. As a professor at the University of Pennsylvania, Duckworth created her own character lab and set out to test her theory.Here, she takes readers into the field to visit teachers working in some of the toughest schools, cadets struggling through their first days at West Point, and young finalists in the National Spelling Bee. She also mines fascinating insights from history and shows what can be gleaned from modern experiments in peak performance. Finally, she shares what she's learned from interviewing dozens of high achievers; from JP Morgan CEO Jamie Dimon to the cartoon editor of The New Yorker to Seattle Seahawks Coach Pete Carroll.Winningly personal, insightful, and even life-changing, Grit is a book about what goes through your head when you fall down, and how that not talent or luck makes all the difference.

    Sapolsky's storytelling concept is delightful but it also has a powerful intrinsic logic: he starts by looking at the factors that bear on a person's reaction in the precise moment a behavior occurs, and then hops back in time from there, in stages, ultimately ending up at the deep history of our species and its evolutionary legacy.And so the first category of explanation is the neurobiological one. A behavior occurs--whether an example of humans at our best, worst, or somewhere in between. What went on in a person's brain a second before the behavior happened? Then Sapolsky pulls out to a slightly larger field of vision, a little earlier in time: What sight, sound, or smell caused the nervous system to produce that behavior? And then, what hormones acted hours to days earlier to change how responsive that individual is to the stimuli that triggered the nervous system? By now he has increased our field of vision so that we are thinking about neurobiology and the sensory world of our environment and endocrinology in trying to explain what happened.Sapolsky keeps going: How was that behavior influenced by structural changes in the nervous system over the preceding months, by that person's adolescence, childhood, fetal life, and then back to his or her genetic makeup? Finally, he expands the view to encompass factors larger than one individual. How did culture shape that individual's group, what ecological factors millennia old formed that culture? And on and on, back to evolutionary factors millions of years old.The result is one of the most dazzling tours d'horizon of the science of human behavior ever attempted, a majestic synthesis that harvests cutting-edge research across a range of disciplines to provide a subtle and nuanced perspective on why we ultimately do the things we do...for good and for ill. Sapolsky builds on this understanding to wrestle with some of our deepest and thorniest questions relating to tribalism and xenophobia, hierarchy and competition, morality and free will, and war and peace. Wise, humane, often very funny, Behave is a towering achievement, powerfully humanizing, and downright heroic in its own right.

    The modern economy—the world itself—relies on technology. Demand for the people who can produce it far outweighs the supply. So why do developers occupy largely subordinate roles in the corporate structure? Developer Hegemony explores the past, present, and future of the corporation and what it means for developers. While it outlines problems with the modern corporate structure, it’s ultimately a play-by-play of how to leave the corporate carnival and control your own destiny. And it’s an emboldening, specific vision of what software development looks like in the world of developer hegemony—one where developers band together into partner firms of “efficiencers,” finally able to command the pay, respect, and freedom that’s earned by solving problems no one else can. Developers, if you grow tired of being treated like geeks who can only be trusted to take orders and churn out code, consider this your call to arms. Bring about the autonomous future that’s rightfully yours. It’s time for developer hegemony.