Pattern Recognition, Learning, and Thought PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Pattern Recognition, Learning, and Thought PDF full book. Access full book title Pattern Recognition, Learning, and Thought by Leonard Merrick Uhr. Download full books in PDF and EPUB format.
Author: Leonard Merrick Uhr
Publisher: Prentice Hall
ISBN:
Category : Computers
Languages : en
Pages : 538
Get Book Here
Book Description
This book stresses the use of learning, and in particular perceptual learning, to develop thinking entities.
Author: Leonard Merrick Uhr
Publisher: Prentice Hall
ISBN:
Category : Computers
Languages : en
Pages : 538
Get Book Here
Book Description
This book stresses the use of learning, and in particular perceptual learning, to develop thinking entities.
Author: Leonard Merrick Uhr
Publisher: Prentice Hall
ISBN:
Category : Computers
Languages : en
Pages : 538
Get Book Here
Book Description
This book stresses the use of learning, and in particular perceptual learning, to develop thinking entities.
Author: Christopher M. Bishop
Publisher: Oxford University Press
ISBN: 0198538642
Category : Computers
Languages : en
Pages : 501
Get Book Here
Book Description
Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.
Author: Christopher M. Bishop
Publisher: Springer
ISBN: 9781493938438
Category : Computers
Languages : en
Pages : 0
Get Book Here
Book Description
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Author: William Gibson
Publisher: Penguin UK
ISBN: 0141904461
Category : Fiction
Languages : en
Pages : 419
Get Book Here
Book Description
'Part-detective story, part-cultural snapshot . . . all bound by Gibson's pin-sharp prose' Arena -------------- THE FIRST NOVEL IN THE BLUE ANT TRILIOGY - READ ZERO HISTORY AND SPOOK COUNTRY FOR MORE Cayce Pollard has a new job. She's been offered a special project: track down the makers of an addictive online film that's lighting up the internet. Hunting the source will take her to Tokyo and Moscow and put her in the sights of Japanese hackers and Russian Mafia. She's up against those who want to control the film, to own it - who figure breaking the law is just another business strategy. The kind of people who relish turning the hunter into the hunted . . . A gripping spy thriller by William Gibson, bestselling author of Neuromancer. Part prophesy, part satire, Pattern Recognition skewers the absurdity of modern life with the lightest and most engaging of touches. Readers of Neal Stephenson, Ray Bradbury and Iain M. Banks won't be able to put this book down. -------------- 'Fast, witty and cleverly politicized' Guardian 'A big novel, full of bold ideas . . . races along like an expert thriller' GQ 'Dangerously hip. Its dialogue and characterization will amaze you. A wonderfully detailed, reckless journey of espionage and lies' USA Today 'A compelling, humane story with a sympathetic heroine searching for meaning and consolation in a post-everything world' Daily Telegraph 'Electric, profound. Gibson's descriptions of Tokyo, Russia and London are surreally spot-on' Financial Times
Author: Jianxin Wu
Publisher: Cambridge University Press
ISBN: 1108483461
Category : Computers
Languages : en
Pages : 401
Get Book Here
Book Description
An accessible undergraduate introduction to the concepts and methods in pattern recognition, machine learning and deep learning.
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392
Get Book Here
Book Description
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Author: Ray Kurzweil
Publisher: Penguin
ISBN: 0143124048
Category : Science
Languages : en
Pages : 353
Get Book Here
Book Description
NEW YORK TIMES BESTSELLER • The bold futurist and renowned author of The Singularity Is Near explores the limitless potential of reverse-engineering the human brain. “This book is a Rosetta Stone for the mystery of human thought.”—Martine Rothblatt, chairman and CEO, United Therapeutics, and creator of Sirius XM Satellite Radio “Kurzweil’s vision of our super-enhanced future is completely sane and calmly reasoned, and his book should nicely smooth the path for the earth’s robot overlords, who, it turns out, will be us.”—The New York Times In How to Create a Mind, Ray Kurzweil presents a provocative exploration of the most important project in human-machine civilization: reverse-engineering the brain to understand precisely how it works and using that knowledge to create even more intelligent machines. Kurzweil discusses how the brain functions, how the mind emerges, brain-computer interfaces, and the implications of vastly increasing the powers of our intelligence to address the world’s problems. He also thoughtfully examines emotional and moral intelligence and the origins of consciousness and envisions the radical possibilities of our merging with the intelligent technology we are creating. Drawing on years of advanced research and cutting-edge inventions in artificial intelligence, How to Create a Mind is an incredible synthesis of neuroscience and technology and provides a road map for the future of human progress.
Author: Richard O. Duda
Publisher: John Wiley & Sons
ISBN: 111858600X
Category : Technology & Engineering
Languages : en
Pages : 680
Get Book Here
Book Description
The first edition, published in 1973, has become a classicreference in the field. Now with the second edition, readers willfind information on key new topics such as neural networks andstatistical pattern recognition, the theory of machine learning,and the theory of invariances. Also included are worked examples,comparisons between different methods, extensive graphics, expandedexercises and computer project topics. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.
Author: Melanie Mitchell
Publisher: Farrar, Straus and Giroux
ISBN: 0374715238
Category : Computers
Languages : en
Pages : 336
Get Book Here
Book Description
Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.
