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.

    Levitin shifts his keen insights from your brain on music to your brain in a sea of details.The information age is drowning us with an unprecedented deluge of data. At the same time, we’re expected to make more—and faster—decisions about our lives than ever before. No wonder, then, that the average American reports frequently losing car keys or reading glasses, missing appointments, and feeling worn out by the effort required just to keep up.But somehow some people become quite accomplished at managing information flow. In The Organized Mind, Daniel J. Levitin, PhD, uses the latest brain science to demonstrate how those people excel—and how readers can use their methods to regain a sense of mastery over the way they organize their homes, workplaces, and time.With lively, entertaining chapters on everything from the kitchen junk drawer to health care to executive office workflow, Levitin reveals how new research into the cognitive neuroscience of attention and memory can be applied to the challenges of our daily lives. This Is Your Brain on Music showed how to better play and appreciate music through an understanding of how the brain works. The Organized Mind shows how to navigate the churning flood of information in the twenty-first century with the same neuroscientific perspective.

    Increasingly, science is concerned with the structure, behavior, and evolution of complex systems ranging from cells to ecosystems. In Networks of the Brain, Olaf Sporns describes how the integrative nature of brain function can be illuminated from a complex network perspective.Highlighting the many emerging points of contact between neuroscience and network science, the book serves to introduce network theory to neuroscientists and neuroscience to those working on theoretical network models. Sporns emphasizes how networks connect levels of organization in the brain and how they link structure to function, offering an informal and nonmathematical treatment of the subject. Networks of the Brain provides a synthesis of the sciences of complex networks and the brain that will be an essential foundation for future research.

    Her story and others like it show that humans are not the only species with the capacity for love, hate, fear, shame, guilt, joy, disgust, and empathy, and open our hearts and minds to the many ways in which humans and other animals are connected. “Through colorful stories and riveting prose, de Waal firmly puts to rest the stubborn notion that humans alone in the animal kingdom experience a broad array of emotions.” — Barbara J. King, NPR“De Waal’s eye- opening observations argue for better treatment and greater appreciation of animals, even as he ensures that you’ll never look at them—or yourself—the same way again.” — People

    In The First Idea, Stanley Greenspan and Stuart Shanker explore this missing link and offer brilliant new insights into two longstanding questions: how human beings first create symbols and how these abilities evolved and were transmitted across generations over millions of years. From fascinating research into the intelligence of both human infants and apes, they identify certain cultural practices that are vitally important if we are to have stable and reflective future societies.

    Since the publication of the award-winning first edition of Evolutionary Psychology, there has been an explosion of research within the field. In this book, David M. Buss examines human behavior from an evolutionary perspective, providing students with the conceptual tools needed to study evolutionary psychology and apply them to empirical research on the human mind. This edition contains expanded coverage of cultural evolution, with a new section on culture–gene co-evolution, additional studies discussing interbreeding between modern humans and Neanderthals, expanded discussions of evolutionary hypotheses that have been empirically disconfirmed, and much more!

    If you want to understand this central quality of human nature to its roots, read Why We Love." —Edward O. WilsonIn Why We Love, renowned anthropologist Helen Fisher offers a new map of the phenomenon of love—from its origins in the brain to the thrilling havoc it creates in our bodies and behavior. Working with a team of scientists to scan the brains of people who had just fallen madly in love, Fisher proved what psychologists had until recently only suspected: when you fall in love, specific areas of the brain "light up" with increased blood flow. This sweeping new book uses this data to argue that romantic passion is hardwired into our brains by millions of years of evolution. It is not an emotion; it is a drive as powerful as hunger.Provocative, enlightening, engaging, and persuasive, Why We Love offers radical new answers to age-old questions: what love is, who we love—and how to keep love alive.

    From one of the world's leading neuroscientists comes a deeply engaging trip into the depths of the human mind.In The Secret Life of the Mind, neuroscientist Mariano Sigman offers a grand yet concise survey of everything you ever wanted to know about how the mind works.From research showing that, even as infants, we are able to form notions of mathematics, language, and morality, to how years and years of formal and informal education can fundamentally change our brains and how we experience the world, The Secret Life of the Mind is an accessible and fascinating overview of neuroscience that will help readers begin to understand even the smallest things that make us who we are.Personal, surprising, and delightfully illuminating, The Secret Life of the Mind is an intimate look into our most intimate selves.

    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.

    With this long-awaited revision, the authors continue to present the theory in a concise and straightforward manner, now with an eye out for the practical applications. They have revised this book to make it more accessible to today's students, including the addition of more material on writing proofs, more figures and pictures to convey ideas, side-boxes to highlight other interesting material, and a less formal writing style. Exercises at the end of each chapter, including some new, easier exercises, help readers confirm and enhance their understanding of the material. *NEW! Completely rewritten to be less formal, providing more accessibility to todays students. *NEW! Increased usage of figures and pictures to help convey ideas. *NEW! More detail and intuition provided for definitions and proofs. *NEW! Provides special side-boxes to present supplemental material that may be of interest to readers. *NEW! Includes more exercises, including many at a lower level. *NEW! Presents program-like notation for PDAs and Turing machines. *NEW! Increas

    The book progresses into a discussion of the Xbox security mechanisms and other advanced hacking topics, with an emphasis on educating the readers on the important subjects of computer security and reverse engineering. Hacking the Xbox includes numerous practical guides, such as where to get hacking gear, soldering techniques, debugging tips and an Xbox hardware reference guide.Hacking the Xbox also confronts the social and political issues facing today's hacker by looking forward and discussing the impact of today's legal challenges on legitimate reverse engineering activities. The book includes a chapter written by the Electronic Frontier Foundation (EFF) about the rights and responsibilities of hackers, and concludes by discussing the latest trends and vulnerabilities in secure PC platforms.

    Nobody is perfect. And that includes five of the greatest scientists in history—Charles Darwin, William Thomson (Lord Kelvin), Linus Pauling, Fred Hoyle, and Albert Einstein. But the mistakes that these great luminaries made helped advance science. Indeed, as Mario Livio explains, science thrives on error, advancing when erroneous ideas are disproven.As a young scientist, Einstein tried to conceive of a way to describe the evolution of the universe at large, based on General Relativity—his theory of space, time, and gravity. Unfortunately he fell victim to a misguided notion of aesthetic simplicity. Fred Hoyle was an eminent astrophysicist who ridiculed an emerging theory about the origin of the universe that he dismissively called “The Big Bang.” The name stuck, but Hoyle was dead wrong in his opposition.They, along with Darwin (a blunder in his theory of Natural Selection), Kelvin (a blunder in his calculation of the age of the earth), and Pauling (a blunder in his model for the structure of the DNA molecule), were brilliant men and fascinating human beings. Their blunders were a necessary part of the scientific process. Collectively they helped to dramatically further our knowledge of the evolution of life, the Earth, and the universe.

    Mind Children, written by an internationally renowned roboticist, offers a comparable experience--a mind-boggling glimpse of a world we may soon share with our artificial progeny. Filled with fresh ideas and insights, this book is one of the most engaging and controversial visions of the future ever written by a serious scholar.Hans Moravec convincingly argues that we are approaching a watershed in the history of life--a time when the boundaries between biological and postbiological intelligence will begin to dissolve. Within forty years, Moravec believes, we will achieve human equivalence in our machines, not only in their capacity to reason but also in their ability to perceive, interact with, and change their complex environment. The critical factor is mobility. A computer rooted to one place is doomed to static iterations, whereas a machine on the prowl, like a mobile organism, must evolve a richer fund of knowledge about an ever-changing world upon which to base its actions.In order to achieve anything near human equivalence, robots will need, at the least, the capacity to perform ten trillion calculations per second. Given the trillion-fold increase in computational power since the end of the nineteenth century, and the promise of exotic technologies far surpassing the now-familiar lasers and even superconductors, Moravec concludes that our hardware will have no trouble meeting this forty-year timetable.But human equivalence is just the beginning, not an upper bound. Once the tireless thinking capacity of robots is directed to the problem of their own improvement and reproduction, even the sky will not limit their voracious exploration of the universe. In the concluding chapters Moravec challenges us to imagine with him the possibilities and pitfalls of such a scenario. Rather than warning us of takeover by robots, the author invites us, as we approach the end of this millennium, to speculate about a plausible, wonderful postbiological future and the ways in which our minds might participate in its unfolding.

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    It is suitable for a one or two semester university course on AI, as well as for researchers in the field.