Probably Approximately Correct

Author : Leslie Valiant
Publisher : Basic Books (AZ)
ISBN 13 : 0465032710
Total Pages : 210 pages
Book Rating : 4.16/5 ( download)

DOWNLOAD NOW!

Download or read book Probably Approximately Correct written by Leslie Valiant and published by Basic Books (AZ). This book was released on 2013-06-04 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting a theory of the theoryless, a computer scientist provides a model of how effective behavior can be learned even in a world as complex as our own, shedding new light on human nature.

Author : Leslie Valiant
Publisher : Basic Books
ISBN 13 : 0465037909
Total Pages : 208 pages
Book Rating : 4.02/5 ( download)

DOWNLOAD NOW!

Download or read book Probably Approximately Correct written by Leslie Valiant and published by Basic Books. This book was released on 2013-06-04 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: We have effective theories for very few things. Gravity is one, electromagnetism another. But for most things—whether as mundane as finding a mate or as major as managing an economy—our theories are lousy or nonexistent. Fortunately, we don't need them, any more than a fish needs a theory of water to swim; we're able to muddle through. But how do we do it? In Probably Approximately Correct, computer scientist Leslie Valiant presents a theory of the theoryless. The key is “probably approximately correct” learning, Valiant's model of how anything can act without needing to understand what is going on. The study of probably approximately correct algorithms reveals the shared computational nature of evolution and cognition, indicates how computers might possess authentic intelligence, and shows why hacking a problem can be far more effective than developing a theory to explain it. After all, finding a mate is a lot more satisfying than finding a theory of mating. Offering an elegant, powerful model that encompasses all of life's complexity, Probably Approximately Correct will revolutionize the way we look at the universe's greatest mysteries.

Author : Leslie Valiant
Publisher : Hachette UK
ISBN 13 : 0465037909
Total Pages : 208 pages
Book Rating : 4.02/5 ( download)

DOWNLOAD NOW!

Download or read book Probably Approximately Correct written by Leslie Valiant and published by Hachette UK. This book was released on 2013-06-04 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: From a leading computer scientist, a unifying theory that will revolutionize our understanding of how life evolves and learns. How does life prosper in a complex and erratic world? While we know that nature follows patterns -- such as the law of gravity -- our everyday lives are beyond what known science can predict. 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.

Author : Michael J. Kearns
Publisher : MIT Press
ISBN 13 : 9780262111935
Total Pages : 230 pages
Book Rating : 4.34/5 ( download)

DOWNLOAD NOW!

Download or read book An Introduction to Computational Learning Theory written by Michael J. Kearns and published by MIT Press. This book was released on 1994-08-15 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.

Author : Shai Shalev-Shwartz
Publisher : Cambridge University Press
ISBN 13 : 1107057132
Total Pages : 415 pages
Book Rating : 4.35/5 ( download)

DOWNLOAD NOW!

Download or read book Understanding Machine Learning written by Shai Shalev-Shwartz and published by Cambridge University Press. This book was released on 2014-05-19 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

Author : David J. C. MacKay
Publisher : Cambridge University Press
ISBN 13 : 9780521642989
Total Pages : 694 pages
Book Rating : 4.81/5 ( download)

DOWNLOAD NOW!

Download or read book Information Theory, Inference and Learning Algorithms written by David J. C. MacKay and published by Cambridge University Press. This book was released on 2003-09-25 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Table of contents

Author : Leslie G. Valiant
Publisher : Oxford University Press, USA
ISBN 13 : 9780195126686
Total Pages : 260 pages
Book Rating : 4.88/5 ( download)

DOWNLOAD NOW!

Download or read book Circuits of the Mind written by Leslie G. Valiant and published by Oxford University Press, USA. This book was released on 2000 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: While embracing the now classical theories of McCulloch and Pitts, the neuroidal model also accommodates state information in the neurons, more flexible timing mechanisms, a variety of assumptions about interconnectivity, and the possibility that different brain areas perform specialized functions. Programmable so that a wide range of algorithmic theories can be described and evaluated, the model provides a concrete computational language and a unified framework in which diverse cognitive phenomena - such as memory, learning, and reasoning - can be systematically and concurrently analyzed. Requiring no specialized knowledge, Circuits of the Mind masterfully offers an exciting new approach to brain science for students and researchers in computer science, neurobiology, neuroscience, artificial intelligence, and cognitive science.

Author : Sunila Gollapudi
Publisher : Packt Publishing Ltd
ISBN 13 : 1784394017
Total Pages : 468 pages
Book Rating : 4.11/5 ( download)

DOWNLOAD NOW!

Download or read book Practical Machine Learning written by Sunila Gollapudi and published by Packt Publishing Ltd. This book was released on 2016-01-30 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tackle the real-world complexities of modern machine learning with innovative, cutting-edge, techniques About This Book Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark Comprehensive practical solutions taking you into the future of machine learning Go a step further and integrate your machine learning projects with Hadoop Who This Book Is For This book has been created for data scientists who want to see machine learning in action and explore its real-world application. With guidance on everything from the fundamentals of machine learning and predictive analytics to the latest innovations set to lead the big data revolution into the future, this is an unmissable resource for anyone dedicated to tackling current big data challenges. Knowledge of programming (Python and R) and mathematics is advisable if you want to get started immediately. What You Will Learn Implement a wide range of algorithms and techniques for tackling complex data Get to grips with some of the most powerful languages in data science, including R, Python, and Julia Harness the capabilities of Spark and Hadoop to manage and process data successfully Apply the appropriate machine learning technique to address real-world problems Get acquainted with Deep learning and find out how neural networks are being used at the cutting-edge of machine learning Explore the future of machine learning and dive deeper into polyglot persistence, semantic data, and more In Detail Finding meaning in increasingly larger and more complex datasets is a growing demand of the modern world. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. Machine learning uses complex algorithms to make improved predictions of outcomes based on historical patterns and the behaviour of data sets. Machine learning can deliver dynamic insights into trends, patterns, and relationships within data, immensely valuable to business growth and development. This book explores an extensive range of machine learning techniques uncovering hidden tricks and tips for several types of data using practical and real-world examples. While machine learning can be highly theoretical, this book offers a refreshing hands-on approach without losing sight of the underlying principles. Inside, a full exploration of the various algorithms gives you high-quality guidance so you can begin to see just how effective machine learning is at tackling contemporary challenges of big data. This is the only book you need to implement a whole suite of open source tools, frameworks, and languages in machine learning. We will cover the leading data science languages, Python and R, and the underrated but powerful Julia, as well as a range of other big data platforms including Spark, Hadoop, and Mahout. Practical Machine Learning is an essential resource for the modern data scientists who want to get to grips with its real-world application. With this book, you will not only learn the fundamentals of machine learning but dive deep into the complexities of real world data before moving on to using Hadoop and its wider ecosystem of tools to process and manage your structured and unstructured data. You will explore different machine learning techniques for both supervised and unsupervised learning; from decision trees to Naive Bayes classifiers and linear and clustering methods, you will learn strategies for a truly advanced approach to the statistical analysis of data. The book also explores the cutting-edge advancements in machine learning, with worked examples and guidance on deep learning and reinforcement learning, providing you with practical demonstrations and samples that help take the theory–and mystery–out of even the most advanced machine learning methodologies. Style and approach A practical data science tutorial designed to give you an insight into the practical application of machine learning, this book takes you through complex concepts and tasks in an accessible way. Featuring information on a wide range of data science techniques, Practical Machine Learning is a comprehensive data science resource.

Author : Ethem Alpaydin
Publisher : MIT Press
ISBN 13 : 0262028182
Total Pages : 639 pages
Book Rating : 4.89/5 ( download)

DOWNLOAD NOW!

Download or read book Introduction to Machine Learning written by Ethem Alpaydin and published by MIT Press. This book was released on 2014-08-22 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.

Author : Dennis Bray
Publisher : Yale University Press
ISBN 13 : 0300155441
Total Pages : 280 pages
Book Rating : 4.40/5 ( download)

DOWNLOAD NOW!

Download or read book Wetware written by Dennis Bray and published by Yale University Press. This book was released on 2009-05-26 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: “A beautifully written journey into the mechanics of the world of the cell, and even beyond, exploring the analogy with computers in a surprising way” (Denis Noble, author of Dance to the Tune of Life). How does a single-cell creature, such as an amoeba, lead such a sophisticated life? How does it hunt living prey, respond to lights, sounds, and smells, and display complex sequences of movements without the benefit of a nervous system? This book offers a startling and original answer. In clear, jargon-free language, Dennis Bray taps the findings from the discipline of systems biology to show that the internal chemistry of living cells is a form of computation. Cells are built out of molecular circuits that perform logical operations, as electronic devices do, but with unique properties. Bray argues that the computational juice of cells provides the basis for all distinctive properties of living systems: it allows organisms to embody in their internal structure an image of the world, and this accounts for their adaptability, responsiveness, and intelligence. In Wetware, Bray offers imaginative, wide-ranging, and perceptive critiques of robotics and complexity theory, as well as many entertaining and telling anecdotes. For the general reader, the practicing scientist, and all others with an interest in the nature of life, this book is an exciting portal to some of biology’s latest discoveries and ideas. “Drawing on the similarities between Pac-Man and an amoeba and efforts to model the human brain, this absorbing read shows that biologists and engineers have a lot to learn from working together.” —Discover magazine “Wetware will get the reader thinking.” —Science magazine