Soon, however, there was talk from Chomsky and his associates about plumbing mental structure; then there was a new phonology; and then there was a new set of goals for the field, cutting it off completely from its anthropological roots and hitching it to a new brand of psychology. Rapidly, all of Chomsky's ideas swept the field. While the entrenched linguists were not looking for a messiah, apparently many of their students were. There was a revolution, which colored the field of linguistics for the following decades. Chomsky's assault on Bloomfieldianism (also known as American Structuralism) and his development of Transformational-Generative Grammar was promptly endorsed by new linguistic recruits swelling the discipline in the sixties. Everyone was talking of a scientific revolution in linguistics, and major breakthroughs seemed imminent, but something unexpected happened--Chomsky and his followers had a vehement and public falling out.In The Linguistic Wars, Randy Allen Harris tells how Chomsky began reevaluating the field and rejecting the extensions his students and erstwhile followers were making. Those he rejected (the Generative Semanticists) reacted bitterly, while new students began to pursue Chomsky's updated vision of language. The result was several years of infighting against the backdrop of the notoriously prickly sixties. The outcome of the dispute, Harris shows, was not simply a matter of a good theory beating out a bad one. The debates followed the usual trajectory of most large-scale clashes, scientific or otherwise. Both positions changed dramatically in the course of the dispute--the triumphant Chomskyan position was very different from the initial one; the defeated generative semantics position was even more transformed. Interestingly, important features of generative semantics have since made their way into other linguistic approaches and continue to influence linguistics to this very day. And fairly high up on the list of borrowers is Noam Chomsky himself. The repercussions of the Linguistics Wars are still with us, not only in the bruised feelings and late-night war stories of the combatants, and in the contentious mood in many quarters, but in the way linguists currently look at language and the mind. Full of anecdotes and colorful portraits of key personalities, The Linguistics Wars is a riveting narrative of the course of an important intellectual controversy, and a revealing look into how scientists and scholars contend for theoretical glory.

    Admittedly, computers now play chess at the grandmaster level, but do they understand the game as we do? Can a computer eventually do everything a human mind can do? In this absorbing and frequently contentious book, Roger Penrose--eminent physicist and winner, with Stephen Hawking, of the prestigious Wolf prize--puts forward his view that there are some facets of human thinking that can never be emulated by a machine. Penrose examines what physics and mathematics can tell us about how the mind works, what they can't, and what we need to know to understand the physical processes of consciousness. He is among a growing number of physicists who think Einstein wasn't being stubborn when he said his little finger told him that quantum mechanics is incomplete, and he concludes that laws even deeper than quantum mechanics are essential for the operation of a mind. To support this contention, Penrose takes the reader on a dazzling tour that covers such topics as complex numbers, Turing machines, complexity theory, quantum mechanics, formal systems, Godel undecidability, phase spaces, Hilbert spaces, black holes, white holes, Hawking radiation, entropy, quasicrystals, the structure of the brain, and scores of other subjects. The Emperor's New Mind will appeal to anyone with a serious interest in modern physics and its relation to philosophical issues, as well as to physicists, mathematicians, philosophers and those on either side of the AI debate.

    Haskell emerged in the last decade as a standard for lazy functional programming, a programming style where arguments are evaluated only when the value is actually needed. Haskell is a marvellous demonstration tool for logic and maths because its functional character allows implementations to remain very close to the concepts that get implemented, while the laziness permits smooth handling of infinite data structures.This book does not assume the reader to have previous experience with either programming or construction of formal proofs, but acquaintance with mathematical notation, at the level of secondary school mathematics is presumed. Everything one needs to know about mathematical reasoning or programming is explained as we go along. After proper digestion of the material in this book the reader will be able to write interesting programs, reason about their correctness, and document them in a clear fashion. The reader will also have learned how to set up mathematical proofs in a structured way, and how to read and digest mathematical proofs written by others.

    Rarely has a book so packed with accurate and well researched factual information been so widely read and popularly acclaimed. It has played a key role in the spread of general interest in language matters, generating further publications and broadcasting events for an avid audience. Its First Edition appeared in hardback in 1995 and a revised paperback in 1997. There have been numerous subsequent updated reprintings; but this Second Edition now presents an overhaul of the subject for a new generation of language-lovers and of teachers, students and professional English-users concerned with their own linguistic legacy.The book offers a unique experience of the English language, exploring its past, present and future. David Crystal systematically explains the history, structure, variety and range of uses of English worldwide, employing a rich apparatus of text, pictures, tables, maps and graphics.The length of the Second Edition has increased by 16 pages and there are 44 new illustrations, a new chapter, extensive new material on world English and Internet English, and a complete updating of statistics, further reading suggestions and other references throughout the book.

    The authors’ expert narrative guides you through each of the essential building blocks of information science offering a concise introduction and expertly chosen further reading and resources. Among the critical topics covered: Foundations, including the information society, historical perspectives and concepts Organizing and retrieving information Information behavior and digital literacies Technologies and digital libraries Information research and methods Changing contexts including publishing, e-science and digital humanities The future of the professionThis is the definitive textbook for students of information science, information and knowledge management, librarianship, archives, and records management worldwide. It’s also an invaluable guide for students of other information-related disciplines such as museum studies, publishing, and information systems. It’s a useful sourcebook for practitioners in all of these disciplines.

    You'll learn how to use Haskell in a variety of practical ways, from short scripts to large and demanding applications. Real World Haskell takes you through the basics of functional programming at a brisk pace, and then helps you increase your understanding of Haskell in real-world issues like I/O, performance, dealing with data, concurrency, and more as you move through each chapter. With this book, you will:Understand the differences between procedural and functional programming Learn the features of Haskell, and how to use it to develop useful programs Interact with filesystems, databases, and network services Write solid code with automated tests, code coverage, and error handling Harness the power of multicore systems via concurrent and parallel programming You'll find plenty of hands-on exercises, along with examples of real Haskell programs that you can modify, compile, and run. Whether or not you've used a functional language before, if you want to understand why Haskell is coming into its own as a practical language in so many major organizations, Real World Haskell is the best place to start.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    This book explains the technical aspects of hacking, including stack based overflows, heap based overflows, string exploits, return-into-libc, shellcode, and cryptographic attacks on 802.11b.

    Not in an editor, IDE, or design tool. You're well educated on how to work with software and hardware, but what about wetware--our own brains? Learning new skills and new technology is critical to your career, and it's all in your head. In this book by Andy Hunt, you'll learn how our brains are wired, and how to take advantage of your brain's architecture. You'll learn new tricks and tips to learn more, faster, and retain more of what you learn. You need a pragmatic approach to thinking and learning. You need to Refactor Your Wetware. Programmers have to learn constantly; not just the stereotypical new technologies, but also the problem domain of the application, the whims of the user community, the quirks of your teammates, the shifting sands of the industry, and the evolving characteristics of the project itself as it is built. We'll journey together through bits of cognitive and neuroscience, learning and behavioral theory. You'll see some surprising aspects of how our brains work, and how you can take advantage of the system to improve your own learning and thinking skills.In this book you'll learn how to:Use the Dreyfus Model of Skill Acquisition to become more expertLeverage the architecture of the brain to strengthen different thinking modesAvoid common "known bugs" in your mindLearn more deliberately and more effectivelyManage knowledge more efficientlyPrinted in full color.

    We nevertheless muddle through even in the absence of theories of how to act. But how do we do it?In Probably Approximately Correct, computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a world as complex as our own. The key is “probably approximately correct” algorithms, a concept Valiant developed to explain how effective behavior can be learned. The model shows that pragmatically coping with a problem can provide a satisfactory solution in the absence of any theory of the problem. After all, finding a mate does not require a theory of mating. Valiant’s theory reveals the shared computational nature of evolution and learning, and sheds light on perennial questions such as nature versus nurture and the limits of artificial intelligence.Offering a powerful and elegant model that encompasses life’s complexity, Probably Approximately Correct has profound implications for how we think about behavior, cognition, biological evolution, and the possibilities and limits of human and machine intelligence.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    This new edition is an extensive revision of the first edition of this successful text. Like the first edition, it surveys the major approaches and methods in language teaching, such as grammar translation, audiolingualism, communicative language teaching, and the natural approach. This edition includes new chapters on topics such as whole language, multiple intelligences, neurolinguistic programming, competency-based language teaching, cooperative language learning, content-based instruction, task-based language teaching, and the Post-Methods Era. Teachers and teachers-in-training will discover that this second edition is a comprehensive survey and analysis of the major and minor teaching methods used around the world.

    A no-nonsense tutorial and reliable reference, this book features thoroughly tested real-world examples. The most important language and library features are demonstrated with deliberately simple sample programs, but they aren't fake and they don't cut corners. More importantly, all of the programs have been updated for J2SE 5.0 and should make good starting points for your own code. You won't find any toy examples here. This is a book for programmers who want to write real code to solve real problems. Cay S. Horstmann is a professor of computer science at San Jose State University. Previously he was vice president and chief technology officer of Preview Systems Inc. and a consultant on C++, Java, and Internet programming for major corporations, universities, and organizations. Gary Cornell has written or cowritten more than twenty popular computer books. He has a Ph.D. from Brown University and has been a visiting scientist at IBM Watson Laboratories, as well as a professor at the University of Connecticut.

    Starting at 'The Beginning' and concluding with 'The End', chapters range from the familiar, such as 'Character', 'Narrative' and 'The Author', to the more unusual, such as 'Secrets', 'Pleasure' and 'Ghosts'. Now in its fifth edition, Bennett and Royle's classic textbook successfully illuminates complex ideas by engaging directly with literary works, so that a reading of Jane Eyre opens up ways of thinking about racial difference, for example, while Chaucer, Raymond Chandler and Monty Python are all invoked in a discussion of literature and laughter.The fifth edition has been revised throughout and includes four new chapters - 'Feelings', 'Wounds', 'Body' and 'Love' - to incorporate exciting recent developments in literary studies. In addition to further reading sections at the end of each chapter, the book contains a comprehensive bibliography and a glossary of key literary terms.A breath of fresh air in a field that can often seem dry and dauntingly theoretical, this book will open the reader's eyes to the exhilarating possibilities of reading and studying literature.

    Myers. Book also includes Social Sense Discovery Channel insert (CD that is sealed)