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.

    He was also a memoirist who wrote with honesty and humor about the remarkable and strange encounters and experiences that shaped him (Uncle Tungsten, On the Move, Gratitude). Sacks, an Oxford-educated polymath, had a deep familiarity not only with literature and medicine but with botany, animal anatomy, chemistry, the history of science, philosophy, and psychology. The River of Consciousness is one of two books Sacks was working on up to his death, and it reveals his ability to make unexpected connections, his sheer joy in knowledge, and his unceasing, timeless project to understand what makes us human.

    The power of an artificial intelligence (AI) comes from its intelligence, not physical strength and laser guns. Humans steer the future not because we're the strongest or the fastest but because we're the smartest. When machines become smarter than humans, we'll be handing them the steering wheel. What promises—and perils—will these powerful machines present? Stuart Armstrong’s new book navigates these questions with clarity and wit.Can we instruct AIs to steer the future as we desire? What goals should we program into them? It turns out this question is difficult to answer! Philosophers have tried for thousands of years to define an ideal world, but there remains no consensus. The prospect of goal-driven, smarter-than-human AI gives moral philosophy a new urgency. The future could be filled with joy, art, compassion, and beings living worthwhile and wonderful lives—but only if we’re able to precisely define what a "good" world is, and skilled enough to describe it perfectly to a computer program.AIs, like computers, will do what we say—which is not necessarily what we mean. Such precision requires encoding the entire system of human values for an AI: explaining them to a mind that is alien to us, defining every ambiguous term, clarifying every edge case. Moreover, our values are fragile: in some cases, if we mis-define a single piece of the puzzle—say, consciousness—we end up with roughly 0% of the value we intended to reap, instead of 99% of the value.Though an understanding of the problem is only beginning to spread, researchers from fields ranging from philosophy to computer science to economics are working together to conceive and test solutions. Are we up to the challenge?A mathematician by training, Armstrong is a Research Fellow at the Future of Humanity Institute (FHI) at Oxford University. His research focuses on formal decision theory, the risks and possibilities of AI, the long term potential for intelligent life (and the difficulties of predicting this), and anthropic (self-locating) probability. Armstrong wrote Smarter Than Us at the request of the Machine Intelligence Research Institute, a non-profit organization studying the theoretical underpinnings of artificial superintelligence.

    if you want to understand how the concept of life is changing, read this' Professor Andrew Briggs, University of OxfordWhen Darwin set out to explain the origin of species, he made no attempt to answer the deeper question: what is life? For generations, scientists have struggled to make sense of this fundamental question. Life really does look like magic: even a humble bacterium accomplishes things so dazzling that no human engineer can match it. And yet, huge advances in molecular biology over the past few decades have served only to deepen the mystery. So can life be explained by known physics and chemistry, or do we need something fundamentally new?In this penetrating and wide-ranging new analysis, world-renowned physicist and science communicator Paul Davies searches for answers in a field so new and fast-moving that it lacks a name, a domain where computing, chemistry, quantum physics and nanotechnology intersect. At the heart of these diverse fields, Davies explains, is the concept of information: a quantity with the power to unify biology with physics, transform technology and medicine, and even to illuminate the age-old question of whether we are alone in the universe.From life's murky origins to the microscopic engines that run the cells of our bodies, The Demon in the Machine is a breath-taking journey across the landscape of physics, biology, logic and computing. Weaving together cancer and consciousness, two-headed worms and bird navigation, Davies reveals how biological organisms garner and process information to conjure order out of chaos, opening a window on the secret of life itself.

    In captivity, octopuses have been known to identify individual human keepers, raid neighboring tanks for food, turn off lightbulbs by spouting jets of water, plug drains, and make daring escapes. How is it that a creature with such gifts evolved through an evolutionary lineage so radically distant from our own? What does it mean that evolution built minds not once but at least twice? The octopus is the closest we will come to meeting an intelligent alien. What can we learn from the encounter?In Other Minds, Peter Godfrey-Smith, a distinguished philosopher of science and a skilled scuba diver, tells a bold new story of how subjective experience crept into being—how nature became aware of itself. As Godfrey-Smith stresses, it is a story that largely occurs in the ocean, where animals first appeared. Tracking the mind’s fitful development, Godfrey-Smith shows how unruly clumps of seaborne cells began living together and became capable of sensing, acting, and signaling. As these primitive organisms became more entangled with others, they grew more complicated. The first nervous systems evolved, probably in ancient relatives of jellyfish; later on, the cephalopods, which began as inconspicuous mollusks, abandoned their shells and rose above the ocean floor, searching for prey and acquiring the greater intelligence needed to do so. Taking an independent route, mammals and birds later began their own evolutionary journeys.But what kind of intelligence do cephalopods possess? Drawing on the latest scientific research and his own scuba-diving adventures, Godfrey-Smith probes the many mysteries that surround the lineage. How did the octopus, a solitary creature with little social life, become so smart? What is it like to have eight tentacles that are so packed with neurons that they virtually “think for themselves”? What happens when some octopuses abandon their hermit-like ways and congregate, as they do in a unique location off the coast of Australia?By tracing the question of inner life back to its roots and comparing human beings with our most remarkable animal relatives, Godfrey-Smith casts crucial new light on the octopus mind—and on our own.