Free Statistical Mechanics Of Learning Ebooks Online
The effort to build machines that are able to learn and undertake tasks such as datamining, image processing and pattern recognition has led to the development of artificial neural networks in which learning from examples may be described and understood. The contribution to this subject made over the past decade by researchers applying the techniques of statistical mechanics is the subject of this book. The authors provide a coherent account of various important concepts and techniques that are currently only found scattered in papers, supplement this with background material in mathematics and physics, and include many examples and exercises.
Paperback: 344 pages
Publisher: Cambridge University Press; 1 edition (April 2, 2001)
Language: English
ISBN-10: 0521774799
ISBN-13: 978-0521774796
Product Dimensions: 6.8 x 0.7 x 9.7 inches
Shipping Weight: 1.6 pounds (View shipping rates and policies)
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Statistical Mechanics of Learning Introduction to Modern Statistical Mechanics The Conceptual Foundations of the Statistical Approach in Mechanics (Dover Books on Physics) Kinetic theory of gases,: With an introduction to statistical mechanics, (International series in physics) Statistical Mechanics, Kinetic Theory and Stochastic Process Statistical Mechanics (Advanced Texts in Physics) Statistical Mechanics, Third Edition Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning series) Statistical Methods for Dynamic Treatment Regimes: Reinforcement Learning, Causal Inference, and Personalized Medicine (Statistics for Biology and Health) The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics) An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics) Statistical Learning with Sparsity: The Lasso and Generalizations (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) Introduction to Statistical Machine Learning RealTime Physics Active Learning Laboratories, Module 1: Mechanics Innovation in Open and Distance Learning: Successful Development of Online and Web-based Learning (Open and Flexible Learning Series) Implementing Cisco IP Routing (ROUTE) Foundation Learning Guide: Foundation learning for the ROUTE 642-902 Exam (Foundation Learning Guides) Implementing Cisco IP Switched Networks (SWITCH) Foundation Learning Guide: Foundation learning for SWITCH 642-813 (Foundation Learning Guides) Deep Learning: Recurrent Neural Networks in Python: LSTM, GRU, and more RNN machine learning architectures in Python and Theano (Machine Learning in Python) Unsupervised Deep Learning in Python: Master Data Science and Machine Learning with Modern Neural Networks written in Python and Theano (Machine Learning in Python) Deep Learning in Python Prerequisites: Master Data Science and Machine Learning with Linear Regression and Logistic Regression in Python (Machine Learning in Python)
