Siracusa's overview, wrap-up, and critique of everything new in OS X 10.10 Yosemite.

    This popular Blueprints book has been refined and updated while keeping the concise, organized style and clinical high-yield content of previous editions. Features include USMLE-style questions and answers with full explanations; Key Points in every section; and a color-enhanced design that increases the usefulness of figures and tables.This edition's completely revised art program includes many additional illustrations. Each chapter in this edition ends with evidence-based references (journals) for students to do additional reading/research.

    For advanced crafters, this book instructs on features such as modes and functions, and teaches how to create with color, texture, and dimension. A cutting guide teaches the perfect settings to cut every type of material. A separate chapter introduces the new features of Cricut Expression™ 2 and explains how it differs from the original Expression machine. More than 50 creative projects inspire ideas for home décor, gifts, parties, cards, and scrapbook layouts.

    

    In eight short chapters it tells a story and invites the reader to join in some up-to-the-minute conceptual discussion of the key issues, problems, and opportunities in cognitive science. The story is about the search for a cognitive scientific understanding of mind. It is presented as a no-holds-barred journey from early work in Artificial Intelligence, through connectionist (artificial neural network) counter-visions, and onto neuroscience artificial life, dynamics and robotics. The journey ends with some wide-ranging and provacative speculation about the role of technology and the changing nature of the human mind itself.Each chapter is organized as an initial sketch of a research program or theme, followed by a substantial discussion section in which specific problems and issues (both familiear and cutting-edge) are raised and pursued. Discussion topics include mental causation, the hardware/software distinction, the relations between life and mind, the nature of perception, cognition and action, and the continuity (or otherwise) of high-level human intelligence with other forms of adaptive response. Classic topics are treated alongside the newer ones in an integrated treatment of the various discussions. The sketches and discussions are accompanied by numerous figures and boxed sections, and followed by suggestions for futher reading.

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

    Consumer's identities are being stolen, and a person's every step is being tracked and stored. What once might have been dismissed as paranoia is now a hard truth, and privacy is a luxury few can afford or understand.In this explosive yet practical book, Kevin Mitnick illustrates what is happening without your knowledge--and he teaches you "the art of invisibility." Mitnick is the world's most famous--and formerly the Most Wanted--computer hacker. He has hacked into some of the country's most powerful and seemingly impenetrable agencies and companies, and at one point he was on a three-year run from the FBI. Now, though, Mitnick is reformed and is widely regarded as the expert on the subject of computer security. He knows exactly how vulnerabilities can be exploited and just what to do to prevent that from happening. In THE ART OF INVISIBILITY Mitnick provides both online and real life tactics and inexpensive methods to protect you and your family, in easy step-by-step instructions. He even talks about more advanced "elite" techniques, which, if used properly, can maximize your privacy. Invisibility isn't just for superheroes--privacy is a power you deserve and need in this modern age.

    Bridging the chasm between educational and social history, this book was one of the first to examine developments in higher education in the context of the social, economic, and political forces that were shaping the nation at large.Surveying higher education from the colonial era through the mid-twentieth century, Rudolph explores a multitude of issues from the financing of institutions and the development of curriculum to the education of women and blacks, the rise of college athletics, and the complexities of student life. In his foreword to this new edition, John Thelin assesses the impact that Rudolph's work has had on higher education studies. The new edition also includes a bibliographic essay by Thelin covering significant works in the field that have appeared since the publication of the first edition.At a time when our educational system as a whole is under intense scrutiny, Rudolph's seminal work offers an important historical perspective on the development of higher education in the United States.

    Chapters parallel most standard pathology texts and each chapter ends with a review test. Topics covered include general and basic pathology, major concepts of disease processes, and systemic pathology surveying principal disorders of each organ system. A comprehensive examination at the end of the book contains 500 USMLE-format questions. USMLE questions have all been updated to current USMLE format.The text is written in outline format for effective review. Icons indicate high-yield information that correlates with key pathology concepts.

    When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning—major trends, possible developments, and significant challenges.

    The constituent technologies discussed comprise neural networks, fuzzy logic, genetic algorithms, and a number of hybrid systems which include classes such as neuro-fuzzy, fuzzy-genetic, and neuro-genetic systems. The hybridization of the technologies is demonstrated on architectures such as Fuzzy-Back-propagation Networks (NN-FL), Simplified Fuzzy ARTMAP (NN-FL), and Fuzzy Associative Memories. The book also gives an exhaustive discussion of FL-GA hybridization. This book with a wealth of information that is clearly presented and illustrated by many examples and applications is designed for use as a text for courses in soft computing at both the senior undergraduate and first-year postgraduate engineering levels.

    For anyone who has ever wondered how computers solve problems, an engagingly written guide for nonexperts to the basics of computer algorithms.

    He is also the Head Teaching Fellow for the most popular course at Harvard, “Positive Psychology,” which is taken by more than 1,000 students per semester and led by Professor Tal Ben-Shahar.  Shawn received his B.A. in English from Harvard and a Master’s from Harvard Divinity School in Christian and Buddhist Ethics. Part of his interest in positive psychology stems from a troubling fact: studies have shown that many of Harvard’s undergraduates suffer from depression at some point in their college careers. One Day University is a unique educational experience  that brings intellectuals together to learn from top rated professors at Yale, Harvard, Stanford, Columbia and other prestigious universities. Chosen for their excellent teaching abilities as rated by their students, these great thinkers represent a wide variety of academic disciplines and share their knowledge in 60 minute, highly entertaining lectures. Offering the ability to learn the highlights of academic thought in world affairs, politics, history, science, art, and more; One Day University is a way to truly enjoy the thrill of learning without the pressures of tests and the high price tag of college tuition. Once reserved only for students who could attend the lectures in New York and other major cities, One Day University courses are now available to everyone from the comfort of their own homes in Kindle format.

    With Mind, Paul Thagard offers an introduction to this interdisciplinary field for readers who come to the subject with very different backgrounds. It is suitable for classroom use by students with interests ranging from computer science and engineering to psychology and philosophy.Thagard's systematic descriptions and evaluations of the main theories of mental representation advanced by cognitive scientists allow students to see that there are many complementary approaches to the investigation of mind. The fundamental theoretical perspectives he describes include logic, rules, concepts, analogies, images, and connections (artificial neural networks). The discussion of these theories provides an integrated view of the different achievements of the various fields of cognitive science.This second edition includes substantial revision and new material. Part I, which presents the different theoretical approaches, has been updated in light of recent work the field. Part II, which treats extensions to cognitive science, has been thoroughly revised, with new chapters added on brains, emotions, and consciousness. Other additions include a list of relevant Web sites at the end of each chapter and a glossary at the end of the book. As in the first edition, each chapter concludes with a summary and suggestions for further reading.

    A step-by-step visual journey through the mathematics of neural networks, and making your own using Python and Tensorflow.