No cloistered don, this tall, married Englishman was a freethinking intellectual. A nudist, he was devoted to quirky folk dancing. In 1937, while working as a biochemist at Cambridge, he fell in love with a visiting Chinese student, with whom he began a lifelong affair. His mistress persuaded him to travel to her home country, where he embarked on a series of expeditions to the frontiers of the ancient empire. He searched for evidence to bolster a conviction that the Chinese were responsible for hundreds of humankind's most familiar innovations—including printing, the compass, explosives, suspension bridges, even toilet paper—often centuries before others. His journeys took him across war-torn China, consolidating his admiration for the Chinese. After the war, he determined to announce what he'd discovered & began writing Science & Civilization in China, describing the country's long history of invention & technology. By the time he died, he'd produced, almost single-handedly, 17 volumes, making him the greatest one-man encyclopedist ever. Epic & intimate, The Man Who Loved China tells the sweeping story of China thru Needham's life. Here's a tale of what makes men, nations & humankind great—related by one of the world's best storytellers.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    In Empires of Light, historian Jill Jonnes portrays this extraordinary trio and their riveting and ruthless world of cutting-edge science, invention, intrigue, money, death, and hard-eyed Wall Street millionaires. At the heart of the story are Thomas Alva Edison, the nation’s most famous and folksy inventor, creator of the incandescent light bulb and mastermind of the world’s first direct current electrical light networks; the Serbian wizard of invention Nikola Tesla, elegant, highly eccentric, a dreamer who revolutionized the generation and delivery of electricity; and the charismatic George Westinghouse, Pittsburgh inventor and tough corporate entrepreneur, an industrial idealist who in the era of gaslight imagined a world powered by cheap and plentiful electricity and worked heart and soul to create it. Edison struggled to introduce his radical new direct current (DC) technology into the hurly-burly of New York City as Tesla and Westinghouse challenged his dominance with their alternating current (AC), thus setting the stage for one of the eeriest feuds in American corporate history, the War of the Electric Currents. The battlegrounds: Wall Street, the 1893 Chicago World’s Fair, Niagara Falls, and, finally, the death chamber - Jonnes takes us on the tense walk down a prison hallway and into the sunlit room where William Kemmler, convicted ax murderer, became the first man to die in the electric chair. Empires of Light is the gripping history of electricity, the “mysterious fluid,” and how the fateful collision of Edison, Tesla, and Westinghouse left the world utterly transformed.

    Describes the five-year, 150 million dollar project Microsoft undertook to develop an advanced PC operating system.

    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.

    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.

    Revolution in the Valley traces this vision back to its earliest roots: the hallways and backrooms of Apple, where the groundbreaking Macintosh computer was born. The book traces the development of the Macintosh, from its inception as an underground skunkworks project in 1979 to its triumphant introduction in 1984 and beyond.The stories in "Revolution in the Valley" come on extremely good authority. That's because author Andy Hertzfeld was a core member of the team that built the Macintosh system software, and a key creator of the Mac's radically new user interface software. One of the chosen few who worked with the mercurial Steve Jobs, you might call him the ultimate insider.When "Revolution in the Valley" begins, Hertzfeld is working on Apple's first attempt at a low-cost, consumer-oriented computer: the Apple II. He sees that Steve Jobs is luring some of the company's most brilliant innovators to work on a tiny research effort the Macintosh. Hertzfeld manages to make his way onto the Macintosh research team, and the rest is history.Through lavish illustrations, period photos, and Hertzfeld's vivid first-hand accounts, Revolution in the Valley reveals what it was like to be there at the birth of the personal computer revolution. The story comes to life through the book's portrait of the talented and often eccentric characters who made up the Macintosh team. Now, over 20 years later, millions of people are benefiting from the technical achievements of this determined and brilliant group of people.

    From the theoretical discussions of nuclear energy to the bright glare of Trinity there was a span of hardly more than twenty-five years. What began as merely an interesting speculative problem in physics grew into the Manhattan Project, and then into the Bomb with frightening rapidity, while scientists known only to their peers -- Szilard, Teller, Oppenheimer, Bohr, Meitner, Fermi, Lawrence, and yon Neumann -- stepped from their ivory towers into the limelight.Richard Rhodes takes us on that journey step by step, minute by minute, and gives us the definitive story of man's most awesome discovery and invention.

    Turing’s openness about his homosexuality at a time when it was an imprisonable offense ultimately led to his untimely lo death at the age of only forty-one. In Alan Turing: Unlocking the Enigma, David Boyle reveals the mysteries behind the man and his remarkable career. Aged just 22, Turing was elected a fellow at King's College, Cambridge on the strength of a dissertation in which he proved the central limit theorem. By the age of 33, he had been awarded the OBE by King George VI for his wartime services: Turing was instrumental in cracking the Nazi Enigma machines at the top secret code breaking establishment at Bletchley Park during the Second World War.But his achievements were to be tragically overshadowed by the paranoia of the post-War years. Hounded for his supposedly subversive views and for his sexuality, Turing was prosecuted in 1952, and forced to accept the humiliation of hormone treatment to avoid a prison sentence. Just two years later, at the age of 41 he was dead. The verdict: cyanide poisoning.Was Turing’s death accidental as his mother always claimed? Or did persistent persecution drive him to take him own life?Alan Turing: Unlocking the Enigma seeks to find the man behind the science, illuminating the life of a person who is still a shadowy presence behind his brilliant achievements.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    Brand explores the exciting programs, and gives readers a look at the future of communications.

    It will take us all back to our roots in the counterculture, and will remind us of the true nature of the innovation process, before we tried to tame it with slogans and buzzwords." -- Po Bronson, #1 New York Times bestselling author of The Nudist on the Late Shift and NurtureshockA candid, colorful, and comprehensive oral history that reveals the secrets of Silicon Valley -- from the origins of Apple and Atari to the present day clashes of Google and Facebook, and all the start-ups and disruptions that happened along the way.Rarely has one economy asserted itself as swiftly--and as aggressively--as the entity we now know as Silicon Valley. Built with a seemingly permanent culture of reinvention, Silicon Valley does not fight change; it embraces it, and now powers the American economy and global innovation. So how did this omnipotent and ever-morphing place come to be? It was not by planning. It was, like many an empire before it, part luck, part timing, and part ambition. And part pure, unbridled genius...Drawing on over two hundred in-depth interviews, VALLEY OF GENIUS takes readers from the dawn of the personal computer and the internet, through the heyday of the web, up to the very moment when our current technological reality was invented. It interweaves accounts of invention and betrayal, overnight success and underground exploits, to tell the story of Silicon Valley like it has never been told before. Read it to discover the stories that Valley insiders tell each other: the tall tales that are all, improbably, true.

      Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems -- it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and -- perhaps even more importantly -- we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

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

    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"