Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    Sold in over 85 countries and translated into more than 5 languages.---------------Want to get started on data science?Our promise: no math added.This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations and visuals.Popular concepts covered include:- A/B Testing- Anomaly Detection- Association Rules- Clustering- Decision Trees and Random Forests- Regression Analysis- Social Network Analysis- Neural NetworksFeatures:- Intuitive explanations and visuals- Real-world applications to illustrate each algorithm- Point summaries at the end of each chapter- Reference sheets comparing the pros and cons of algorithms- Glossary list of commonly-used termsWith this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions.

    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.

    Verification that algorithms work is emphasized more than their complexity. An effective use of examples, and huge number of interesting exercises, demonstrate the topics of trees and distance, matchings and factors, connectivity and paths, graph coloring, edges and cycles, and planar graphs. For those who need to learn to make coherent arguments in the fields of mathematics and computer science.

    These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

    Thompson tells the dramatic story of one of the most successful research aircraft ever flown. The first full-length account of the X-15 program, the book profiles the twelve test pilots (Neil Armstrong, Joe Engle, Scott Crossfield, and the author among them) chosen for the program. Thompson has translated a highly technical subject into readable accounts of each pilot's participation, including many heroic and humorous anecdotes and highlighting the pilots' careers after the program ended in 1968.

    Imagine that you face three doors, behind one of which is a prize. You choose one but do not open it. The host--call him Monty Hall--opens a different door, alwayschoosing one he knows to be empty. Left with two doors, will you do better by sticking with your first choice, or by switching to the other remaining door? In this light-hearted yet ultimately serious book, Jason Rosenhouse explores the history of this fascinating puzzle. Using a minimum ofmathematics (and none at all for much of the book), he shows how the problem has fascinated philosophers, psychologists, and many others, and examines the many variations that have appeared over the years. As Rosenhouse demonstrates, the Monty Hall Problem illuminates fundamental mathematical issuesand has abiding philosophical implications. Perhaps most important, he writes, the problem opens a window on our cognitive difficulties in reasoning about uncertainty.

    Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data.

    The victory of IBM's Watson on the television quiz show Jeopardy! revealed how scientists and engineers at IBM and elsewhere are pushing the boundaries of science and technology to create machines that sense, learn, reason, and interact with people in new ways to provide insight and advice.In Smart Machines, John E. Kelly III, director of IBM Research, and Steve Hamm, a writer at IBM and a former business and technology journalist, introduce the fascinating world of "cognitive systems" to general audiences and provide a window into the future of computing. Cognitive systems promise to penetrate complexity and assist people and organizations in better decision making. They can help doctors evaluate and treat patients, augment the ways we see, anticipate major weather events, and contribute to smarter urban planning. Kelly and Hamm's comprehensive perspective describes this technology inside and out and explains how it will help us conquer the harnessing and understanding of "big data," one of the major computing challenges facing businesses and governments in the coming decades. Absorbing and impassioned, their book will inspire governments, academics, and the global tech industry to work together to power this exciting wave in innovation.

    From Gary to Greatness. In his first book in 14 years, the living pop-icon gives an exclusive insight into his private photo archive. My World contains lots of never before seen photographs of Jackson, from 1980 to 2006. Jackson also opens up the doors to his work as the world's most brillant artist (2002 American Music Awards: Artist of the Century) by publishing his hand-written lyrics to his world-famous smash hits Billie Jean, Bad, Black or White, and Smooth Criminal. Moreover the book features personal thoughts and rarely seen lyrics by Jackson along with the high quality pictures of Jackson's dance, stage shows, private life, and public appearances that show the true genius and achievements of music's biggest icon: Michael Jackson.

    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.

    "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    It now has 600,000 to a million page hits daily. Every now and then, Munroe would get emails asking him to arbitrate a science debate. 'My friend and I were arguing about what would happen if a bullet got struck by lightning, and we agreed that you should resolve it . . . ' He liked these questions so much that he started up What If. If your cells suddenly lost the power to divide, how long would you survive? How dangerous is it, really, to be in a swimming pool in a thunderstorm? If we hooked turbines to people exercising in gyms, how much power could we produce? What if everyone only had one soulmate?When (if ever) did the sun go down on the British empire? How fast can you hit a speed bump while driving and live?What would happen if the moon went away?In pursuit of answers, Munroe runs computer simulations, pores over stacks of declassified military research memos, solves differential equations, and consults with nuclear reactor operators. His responses are masterpieces of clarity and hilarity, studded with memorable cartoons and infographics. They often predict the complete annihilation of humankind, or at least a really big explosion. Far more than a book for geeks, WHAT IF: Serious Scientific Answers to Absurd Hypothetical Questions explains the laws of science in operation in a way that every intelligent reader will enjoy and feel much the smarter for having read.

    Blade Runner, The Matrix, Star Wars, Avatar, Star Trek, Ready Player One and Avengers show us futuristic worlds where holograms, intelligent robots, smart devices, virtual avatars, digital transactions, and universe-scale teleportation work together perfectly, somehow seamlessly combining the virtual and the physical with the mechanical and the biological. Science fiction has done an excellent job describing a vision of the future where the digital and physical merge naturally into one — in a way that just works everywhere, for everyone. However, none of these visionary fictional works go so far as to describe exactly how this would actually be accomplished. While it has inspired many of us to ask the question—How do we enable science fantasy to become....science fact? The Spatial Web achieves this by first describing how exponentially powerful computing technologies are creating a great “Convergence.” How Augmented and Virtual Reality will enable us to overlay our information and imaginations onto the world. How Artificial Intelligence will infuse the environments and objects around us with adaptive intelligence. How the Internet of Things and Robotics will enable our vehicles, appliances, clothing, furniture, and homes to become connected and embodied with the power to see, feel, hear, smell, touch and move things in the world, and how Blockchain and Cryptocurrencies will secure our data and enable real-time transactions between the human, machine and virtual economies of the future. The book then dives deeply into the challenges and shortcomings of the World Wide Web, the rise of fake news and surveillance capitalism in Web 2.0 and the risk of algorithmic terrorism and biological hacking and “fake-reality” in Web 3.0. It raises concerns about the threat that emerging technologies pose in the hands of rogue actors whether human, algorithmic, corporate or state-sponsored and calls for common sense governance and global cooperation. It calls for business leaders, organizations and governments to not only support interoperable standards for software code, but critically, for ethical, and social codes as well. Authors Gabriel René and Dan Mapes describe in vivid detail how a new “spatial” protocol is required in order to connect the various exponential technologies of the 21st century into an integrated network capable of tracking and managing the real-time activities of our cities, monitoring and adjusting the supply chains that feed them, optimizing our farms and natural resources, automating our manufacturing and distribution, transforming marketing and commerce, accelerating our global economies, running advanced planet-scale simulations and predictions, and even bridging the gap between our interior individual reality and our exterior collective one. Enabling the ability for humans, machines and AI to communicate, collaborate and coordinate activities in the world at a global scale and how the thoughtful application of these technologies could lead to an unprecedented opportunity to create a truly global “networked” civilization or "Smart World.” The book artfully shifts between cyberpunk futurism, cautionary tale-telling, and life-affirming call-to-arms. It challenges us to consider the importance of today’s technological choices as individuals, organizations, and as a species, as we face the historic opportunity we have to transform the web, the world, and our very definition of reality.