Now, physicist Leonard Susskind has teamed up with data engineer Art Friedman to present the theory and associated mathematics of the strange world of quantum mechanics.In this follow-up to The Theoretical Minimum, Susskind and Friedman provide a lively introduction to this famously difficult field, which attempts to understand the behavior of sub-atomic objects through mathematical abstractions. Unlike other popularizations that shy away from quantum mechanics’ weirdness, Quantum Mechanics embraces the utter strangeness of quantum logic. The authors offer crystal-clear explanations of the principles of quantum states, uncertainty and time dependence, entanglement, and particle and wave states, among other topics, and each chapter includes exercises to ensure mastery of each area. Like The Theoretical Minimum, this volume runs parallel to Susskind’s eponymous Stanford University-hosted continuing education course.An approachable yet rigorous introduction to a famously difficult topic, Quantum Mechanics provides a tool kit for amateur scientists to learn physics at their own pace.

    Having just completed his masterpiece, The General Theory of Relativity—which provided a brand-new theory of gravity and promised a new perspective on the cosmos as a whole—he set out at once to share his excitement with as wide a public as possible in this popular and accessible book.Here published for the first time as a Penguin Classic, this edition of Relativity features a new introduction by bestselling science author Nigel Calder.

    Cases, datasets, and examples allow for a more real-world perspective and explore relevant uses of regression techniques in business today.

    Traces the history of time from Augustine's suggestion that there is no time, to the flowing time of Newton, the static time of Einstein, and then back, to the idea that there is no time in quantum gravity.

    Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    Introducing Feminism surveys the major developments that have affected women's lives from the seventeenth century to the present day."Readers who have forgotten the struggles of women who came generations—and centuries—before will appreciate this handsome little guide introducing the basics of feminist theory. Although far from an academic study, the cartoon-drawing format and merry black-and-white illustrations will render the book popular among younger groups in need of a rapid overview of the movement. From Mary Wollstonecraft to Betty Friedan, the diminutive volume offers a chronological history of feminism in its nascent roots in colonial times, to the 1960s Women's Movement and its modern form today. Most notable, the book places a large emphasis on the struggles of African-American women, highlighting the lives and careers of such activists as Sojourner Truth, Harriet Tubman, bell hooks and Audre Lorde. Another standout section covers Germaine Greer, a proponent of the idea that 'heterosexuality is a form of oppression, conditioning women to conform to their society's expectations of femininity and encouraging them to believe that their value depends on their appeal to men.'"— Kirkus Reviews

    Born in Vienna in 1882, Melanie Klein became a pioneer in child psychoanalysis and developed several ground-breaking concepts about the nature and crucial importance of the early stages of infantile development. Although she was a devoted Freudian, many of her ideas were seen within the psychoanalytic movement as highly controversial, and this led to heated conflicts, particularly with Freud's daughter, Anna. Introducing Melanie Klein brilliantly explains Klein's ideas, and shows the importance of her startling discoveries which raised such opposition at the time and are only now being recognized for their explanatory power. Her concepts of the depressive position and the paranoid-schizoid position are now in common usage and her work has to be taken seriously by psychoanalysts the world over. She is also now important in many academic fields within the human sciences.

    The Art of Problem Solving, Volume 2, is the classic problem solving textbook used by many successful high school math teams and enrichment programs and have been an important building block for students who, like the authors, performed well enough on the American Mathematics Contest series to qualify for the Math Olympiad Summer Program which trains students for the United States International Math Olympiad team.Volume 2 is appropriate for students who have mastered the problem solving fundamentals presented in Volume 1 and are ready for a greater challenge. Although the Art of Problem Solving is widely used by students preparing for mathematics competitions, the book is not just a collection of tricks. The emphasis on learning and understanding methods rather than memorizing formulas enables students to solve large classes of problems beyond those presented in the book.Speaking of problems, the Art of Problem Solving, Volume 2, contains over 500 examples and exercises culled from such contests as the Mandelbrot Competition, the AMC tests, and ARML. Full solutions (not just answers!) are available for all the problems in the solution manual.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    But sometimes the solutions are not as interesting as the beautiful symmetric patterns that lead to them. Written in a friendly style for a general audience, Fearless Symmetry is the first popular math book to discuss these elegant and mysterious patterns and the ingenious techniques mathematicians use to uncover them.Hidden symmetries were first discovered nearly two hundred years ago by French mathematician �variste Galois. They have been used extensively in the oldest and largest branch of mathematics--number theory--for such diverse applications as acoustics, radar, and codes and ciphers. They have also been employed in the study of Fibonacci numbers and to attack well-known problems such as Fermat's Last Theorem, Pythagorean Triples, and the ever-elusive Riemann Hypothesis. Mathematicians are still devising techniques for teasing out these mysterious patterns, and their uses are limited only by the imagination.The first popular book to address representation theory and reciprocity laws, Fearless Symmetry focuses on how mathematicians solve equations and prove theorems. It discusses rules of math and why they are just as important as those in any games one might play. The book starts with basic properties of integers and permutations and reaches current research in number theory. Along the way, it takes delightful historical and philosophical digressions. Required reading for all math buffs, the book will appeal to anyone curious about popular mathematics and its myriad contributions to everyday life.

    Your online and in-store purchasing patterns are recorded, and reveal if you're unemployed, sick, or pregnant. Your e-mails and texts expose your intimate and casual friends. Google knows what you’re thinking because it saves your private searches. Facebook can determine your sexual orientation without you ever mentioning it.The powers that surveil us do more than simply store this information. Corporations use surveillance to manipulate not only the news articles and advertisements we each see, but also the prices we’re offered. Governments use surveillance to discriminate, censor, chill free speech, and put people in danger worldwide. And both sides share this information with each other or, even worse, lose it to cybercriminals in huge data breaches.Much of this is voluntary: we cooperate with corporate surveillance because it promises us convenience, and we submit to government surveillance because it promises us protection. The result is a mass surveillance society of our own making. But have we given up more than we’ve gained? In Data and Goliath, security expert Bruce Schneier offers another path, one that values both security and privacy. He brings his bestseller up-to-date with a new preface covering the latest developments, and then shows us exactly what we can do to reform government surveillance programs, shake up surveillance-based business models, and protect our individual privacy. You'll never look at your phone, your computer, your credit cards, or even your car in the same way again.

    But in our zeal to instill the evaluation process with scientific rigor, we've gone from measuring performance to fixating on measuring itself. The result is a tyranny of metrics that threatens the quality of our lives and most important institutions. In this timely and powerful book, Jerry Muller uncovers the damage our obsession with metrics is causing--and shows how we can begin to fix the problem.Filled with examples from education, medicine, business and finance, government, the police and military, and philanthropy and foreign aid, this brief and accessible book explains why the seemingly irresistible pressure to quantify performance distorts and distracts, whether by encouraging "gaming the stats" or "teaching to the test." That's because what can and does get measured is not always worth measuring, may not be what we really want to know, and may draw effort away from the things we care about. Along the way, we learn why paying for measured performance doesn't work, why surgical scorecards may increase deaths, and much more. But metrics can be good when used as a complement to--rather than a replacement for--judgment based on personal experience, and Muller also gives examples of when metrics have been beneficial.Complete with a checklist of when and how to use metrics, The Tyranny of Metrics is an essential corrective to a rarely questioned trend that increasingly affects us all.

    A simple web search picks out a handful of relevant needles from the world's biggest haystack: the billions of pages on the World Wide Web. Uploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers; and we use digital signatures to verify the identity of the websites we visit. How do our computers perform these tasks with such ease? This is the first book to answer that question in language anyone can understand, revealing the extraordinary ideas that power our PCs, laptops, and smartphones. Using vivid examples, John MacCormick explains the fundamental "tricks" behind nine types of computer algorithms, including artificial intelligence (where we learn about the "nearest neighbor trick" and "twenty questions trick"), Google's famous PageRank algorithm (which uses the "random surfer trick"), data compression, error correction, and much more. These revolutionary algorithms have changed our world: this book unlocks their secrets, and lays bare the incredible ideas that our computers use every day.

    This entertaining guide builds on scores of case studies taken from business, sports, the movies, politics, and gambling. It outlines the basics of good strategy making and then shows how you can apply them in any area of your life.

    Whether pondering black holes or predicting discoveries at CERN, physicists believe the best theories are beautiful, natural, and elegant, and this standard separates popular theories from disposable ones. This is why, Sabine Hossenfelder argues, we have not seen a major breakthrough in the foundations of physics for more than four decades. The belief in beauty has become so dogmatic that it now conflicts with scientific objectivity: observation has been unable to confirm mindboggling theories, like supersymmetry or grand unification, invented by physicists based on aesthetic criteria. Worse, these "too good to not be true" theories are actually untestable and they have left the field in a cul-de-sac. To escape, physicists must rethink their methods. Only by embracing reality as it is can science discover the truth.