But ask what it means, and the result will be a brawl. For a century, most physicists have followed Niels Bohr's Copenhagen interpretation and dismissed questions about the reality underlying quantum physics as meaningless. A mishmash of solipsism and poor reasoning, Copenhagen endured, as Bohr's students vigorously protected his legacy, and the physics community favored practical experiments over philosophical arguments. As a result, questioning the status quo long meant professional ruin. And yet, from the 1920s to today, physicists like John Bell, David Bohm, and Hugh Everett persisted in seeking the true meaning of quantum mechanics. What Is Real? is the gripping story of this battle of ideas and of the courageous scientists who dared to stand up for truth.

    He shows that the scientists of ancient and medieval times not only did not understand what we understand about the world—they did not understand what there is to understand, or how to understand it. Yet over the centuries, through the struggle to solve such mysteries as the curious backward movement of the planets and the rise and fall of the tides, the modern discipline of science eventually emerged. Along the way, Weinberg examines historic clashes and collaborations between science and the competing spheres of religion, technology, poetry, mathematics, and philosophy.An illuminating exploration of the way we consider and analyze the world around us, To Explain the World is a sweeping, ambitious account of how difficult it was to discover the goals and methods of modern science, and the impact of this discovery on human knowledge and development.

    During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.

    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.

    Through the lives of Geoff Hinton and other major players, Metz explains this transformative technology and makes the quest thrilling.--Walter Isaacson, author of The Code Breaker Recipient of starred reviews in both Kirkus and Library JournalTHE UNTOLD TECH STORY OF OUR TIMEWhat does it mean to be smart? To be human? What do we really want from life and the intelligence we have, or might create?With deep and exclusive reporting, across hundreds of interviews, New York Times Silicon Valley journalist Cade Metz brings you into the rooms where these questions are being answered. Where an extraordinarily powerful new artificial intelligence has been built into our biggest companies, our social discourse, and our daily lives, with few of us even noticing.Long dismissed as a technology of the distant future, artificial intelligence was a project consigned to the fringes of the scientific community. Then two researchers changed everything. One was a sixty-four-year-old computer science professor who didn't drive and didn't fly because he could no longer sit down--but still made his way across North America for the moment that would define a new age of technology. The other was a thirty-six-year-old neuroscientist and chess prodigy who laid claim to being the greatest game player of all time before vowing to build a machine that could do anything the human brain could do.They took two very different paths to that lofty goal, and they disagreed on how quickly it would arrive. But both were soon drawn into the heart of the tech industry. Their ideas drove a new kind of arms race, spanning Google, Microsoft, Facebook, and OpenAI, a new lab founded by Silicon Valley kingpin Elon Musk. But some believed that China would beat them all to the finish line.Genius Makers dramatically presents the fierce conflict between national interests, shareholder value, the pursuit of scientific knowledge, and the very human concerns about privacy, security, bias, and prejudice. Like a great Victorian novel, this world of eccentric, brilliant, often unimaginably yet suddenly wealthy characters draws you into the most profound moral questions we can ask. And like a great mystery, it presents the story and facts that lead to a core, vital question:How far will we let it go?

    Along the way, we encounter black holes, turtles, snakes, dragons, axe-sharpening, and yak-shaving—and take a guided tour through the theories and methods, both brilliant and misguided, that litter the history of software development, from the famous ‘mythical man-month’ to Extreme Programming. Not just for technophiles but for anyone captivated by the drama of invention, Dreaming in Code offers a window into both the information age and the workings of the human mind.

    If we get it right it will make humans almost godlike. If we get it wrong... well, extinction is not the worst possible outcome.“Surviving AI” is a concise, easy-to-read guide to what's coming, taking you through technological unemployment (the economic singularity) and the possible creation of a superintelligence (the technological singularity).Here's what some of the leading thinkers in the field have to say about it:A sober and easy-to-read review of the risks and opportunities that humanity will face from AI. Jaan Tallinn – co-founder of Skype Understanding AI – its promise and its dangers – is emerging as one of the great challenges of coming decades and this is an invaluable guide to anyone who’s interested, confused, excited or scared. David Shukman – BBC Science Editor We have recently seen a surge in the volume of scholarly analysis of this topic; Chace impressively augments that with this high-quality, more general-audience discussion. Aubrey de Grey – CSO of SENS Research Foundation; former AI researcher It's rare to see a book about the potential End of the World that is fun to read without descending into sensationalism or crass oversimplification. Ben Goertzel – chairman of Novamente LLC Calum Chace is a prescient messenger of the risks and rewards of artificial intelligence. In “Surviving AI” he has identified the most essential issues and developed them with insight and wit – so that the very framing of the questions aids our search for answers. Chace’s sensible balance between AI’s promise and peril makes “Surviving AI” an excellent primer for anyone interested in what’s happening, how we got here, and where we are headed. Kenneth Cukier – co-author of “Big Data” If you’re not thinking about AI, you’re not thinking.  “Surviving AI” combines an essential grounding in the state of the art with a survey of scenarios that will be discussed with equal vigor at cocktail parties and academic colloquia. Chris Meyer – author of “Blur”, “It’s Alive”, and “Standing on the Sun” The appearance of Calum Chace's book is of some considerable personal satisfaction to me, because it signifies the fact that the level of social awareness of the rise of massively intelligent machines has finally reached the mainstream. If you want to survive the next few decades, you cannot afford NOT to read Chace's book. Prof. Dr. Hugo de Garis – former director of the Artificial Brain Lab, Xiamen University, China “Surviving AI” is an exceptionally clear, well-researched and balanced introduction to a complex and controversial topic, and is a compelling read to boot. Seán Ó hÉigeartaigh – executive director of Cambridge Centre for the Study of Existential Risk In “Surviving AI”, Calum Chace provides a marvellously accessible guide to the swirls of controversy that surround discussion of what is likely to be the single most important event in human history - the emergence of artificial super