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Books like Neural networks for pattern recognition by Christopher M. Bishop

Name: Neural networks for pattern recognition
Rating: 4 (1 reviews)
Author: Christopher M. Bishop

📘 Neural networks for pattern recognition by Christopher M. Bishop

First publish date: 1995

Genre: Technology & Computing/Artificial Intelligence

Authors: Christopher M. Bishop

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Books similar to Neural networks for pattern recognition (7 similar books)

📘 Deep Learning

by Ian Goodfellow

Deep Learning is a comprehensive textbook that equips students and practitioners with the foundational knowledge and practical skills needed to enter the fields of machine learning and deep learning.

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📘 Neural networks for vision and image processing

by Gail A. Carpenter

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📘 Pattern Recognition and Machine Learning (Information Science and Statistics)

by Christopher M. Bishop

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📘 Neural Networks and Fuzzy Systems

by Bart Kosko

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📘 Pattern classification

by Richard O. Duda

A practical guide for professionals and researchers to select and apply the most suitable pattern recognition techniques across domains like speech, OCR, and image processing.

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📘 Talking nets

by Anderson, James A.

Since World War II, a group of scientists has been attempting to understand the human nervous system and to build computer systems that emulate the brian's abilities. Many of the workers in this field of neural networks came from cybernetics; others came from neuroscience, physics, electrical engineering, mathematics, psychology, even economics. In this collection of interviews, those who helped to shape the field share their childhood memories, their influences, how they became interested in neural networks, and how they envision its future.

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📘 Pattern Recognition and Machine Learning

by Christopher M. Bishop

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Some Other Similar Books

The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, Jerome Friedman
Machine Learning: A Probabilistic Perspective by Kevin P. Murphy
Neural Network Methods in Pattern Recognition by Kevin G. J. McGregor
Artificial Neural Networks: A Beginner's Guide by Kevin Gurney
Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz, Shai Ben-David
Fundamentals of Neural Networks: Architectures, Algorithms and Applications by Liang-Jie Zhang
Introduction to Pattern Recognition: A MATLAB Approach by Sergios Theodoridis

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