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Pattern Recognition, Learning, and Thought

Pattern Recognition, Learning, and Thought
Author: Leonard Merrick Uhr
Publisher: Prentice Hall
Total Pages: 538
Release: 1973
Genre: Computers
ISBN:

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This book stresses the use of learning, and in particular perceptual learning, to develop thinking entities.


Pattern Recognition, Learning, and Thought

Pattern Recognition, Learning, and Thought
Author: Leonard Merrick Uhr
Publisher: Prentice Hall
Total Pages: 538
Release: 1973
Genre: Computers
ISBN:

Download Pattern Recognition, Learning, and Thought Book in PDF, ePub and Kindle

This book stresses the use of learning, and in particular perceptual learning, to develop thinking entities.


Neural Networks for Pattern Recognition

Neural Networks for Pattern Recognition
Author: Christopher M. Bishop
Publisher: Oxford University Press
Total Pages: 501
Release: 1995-11-23
Genre: Computers
ISBN: 0198538642

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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.


Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning
Author: Christopher M. Bishop
Publisher: Springer
Total Pages: 0
Release: 2016-08-23
Genre: Computers
ISBN: 9781493938438

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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.


Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning
Author: Y. Anzai
Publisher: Elsevier
Total Pages: 424
Release: 2012-12-02
Genre: Computers
ISBN: 0080513638

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This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.


Pattern Recognition

Pattern Recognition
Author: William Gibson
Publisher: Penguin UK
Total Pages: 419
Release: 2004-06-24
Genre: Fiction
ISBN: 0141904461

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'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


Mathematics for Machine Learning

Mathematics for Machine Learning
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
Total Pages: 392
Release: 2020-04-23
Genre: Computers
ISBN: 1108569323

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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.


Essentials of Pattern Recognition

Essentials of Pattern Recognition
Author: Jianxin Wu
Publisher: Cambridge University Press
Total Pages: 401
Release: 2020-11-19
Genre: Computers
ISBN: 1108483461

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An accessible undergraduate introduction to the concepts and methods in pattern recognition, machine learning and deep learning.


Pattern Recognition and Neural Networks

Pattern Recognition and Neural Networks
Author: Brian D. Ripley
Publisher: Cambridge University Press
Total Pages: 420
Release: 2007
Genre: Computers
ISBN: 9780521717700

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This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.