Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning
Author: Christopher M. Bishop
Publsiher: Springer
Total Pages: 738
Release: 2016-08-23
Genre: Computers
ISBN: 1493938436

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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: Christopher M. Bishop
Publsiher: Springer Verlag
Total Pages: 738
Release: 2006-08-17
Genre: Computers
ISBN: 0387310738

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This is the first text on pattern recognition to present the Bayesian viewpoint, one that has become increasing popular in the last five years. It presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It provides the first text to use graphical models to describe probability distributions when there are no other books that apply graphical models to machine learning. It is also the first four-color book on pattern recognition. The book is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. Extensive support is provided for course instructors, including more than 400 exercises, graded according to difficulty. Example solutions for a subset of the exercises are available from the book web site, while solutions for the remainder can be obtained by instructors from the publisher.

Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning
Author: Christopher M. Bishop
Publsiher: Unknown
Total Pages: 738
Release: 2013
Genre: Machine learning
ISBN: 8132209060

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The field of pattern recognition has undergone substantial development over the years. This book reflects these developments while providing a grounding in the basic concepts of pattern recognition and machine learning. It is aimed at advanced undergraduates or first year PhD students, as well as researchers and practitioners.

Pattern Recognition and Machine Intelligence

Pattern Recognition and Machine Intelligence
Author: B. Uma Shankar,Kuntal Ghosh,Deba Prasad Mandal,Shubhra Sankar Ray,David Zhang,Sankar K. Pal
Publsiher: Springer
Total Pages: 695
Release: 2017-11-22
Genre: Computers
ISBN: 9783319699004

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This book constitutes the proceedings of the 7th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2017,held in Kolkata, India, in December 2017. The total of 86 full papers presented in this volume were carefully reviewed and selected from 293 submissions. They were organized in topical sections named: pattern recognition and machine learning; signal and image processing; computer vision and video processing; soft and natural computing; speech and natural language processing; bioinformatics and computational biology; data mining and big data analytics; deep learning; spatial data science and engineering; and applications of pattern recognition and machine intelligence.

Fundamentals of Pattern Recognition and Machine Learning

Fundamentals of Pattern Recognition and Machine Learning
Author: Ulisses Braga-Neto
Publsiher: Springer Nature
Total Pages: 357
Release: 2020-09-10
Genre: Computers
ISBN: 9783030276560

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Fundamentals of Pattern Recognition and Machine Learning is designed for a one or two-semester introductory course in Pattern Recognition or Machine Learning at the graduate or advanced undergraduate level. The book combines theory and practice and is suitable to the classroom and self-study. It has grown out of lecture notes and assignments that the author has developed while teaching classes on this topic for the past 13 years at Texas A&M University. The book is intended to be concise but thorough. It does not attempt an encyclopedic approach, but covers in significant detail the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as Gaussian process regression and convolutional neural networks. In addition, the selection of topics has a few features that are unique among comparable texts: it contains an extensive chapter on classifier error estimation, as well as sections on Bayesian classification, Bayesian error estimation, separate sampling, and rank-based classification. The book is mathematically rigorous and covers the classical theorems in the area. Nevertheless, an effort is made in the book to strike a balance between theory and practice. In particular, examples with datasets from applications in bioinformatics and materials informatics are used throughout to illustrate the theory. These datasets are available from the book website to be used in end-of-chapter coding assignments based on python and scikit-learn. All plots in the text were generated using python scripts, which are also available on the book website.

Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning
Author: Y. Anzai
Publsiher: Elsevier
Total Pages: 407
Release: 2012-12-02
Genre: Computers
ISBN: 9780080513638

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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 and Machine Intelligence

Pattern Recognition and Machine Intelligence
Author: Pradipta Maji,Ashish Ghosh,M. Narasimha Murty,Kuntal Ghosh,Sankar K. Pal
Publsiher: Springer
Total Pages: 753
Release: 2013-12-09
Genre: Computers
ISBN: 9783642450624

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This book constitutes the refereed proceedings of the 5th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2013, held in Kolkata, India in December 2013. The 101 revised papers presented together with 9 invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on pattern recognition; machine learning; image processing; speech and video processing; medical imaging; document image processing; soft computing; bioinformatics and computational biology; and social media mining.

Machine Learning in Image Analysis and Pattern Recognition

Machine Learning in Image Analysis and Pattern Recognition
Author: Munish Kumar , R. K. Sharma,Ishwar Sethi
Publsiher: MDPI
Total Pages: 112
Release: 2021-09-08
Genre: Technology & Engineering
ISBN: 9783036517148

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This book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. In this book, we have assembled original research articles making unique contributions to the theory, methodology and applications of machine learning in image analysis and pattern recognition.