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robotics.stanford.edu
This is an introductory book about machine learning. Notice that this is a draft book....
Nils J. Nilsson
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www.cedar.buffalo.edu
"Pattern recognition techniques are concerned with the theory and algorithms of putting abstract objects, e.g., measurements made on physical objects, into categories. Typically the categories are assumed to be known in advance, although there are techniques to learn the categories (clustering)....
Sargur Srihari
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2
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www.amsta.leeds.ac.uk
This book covers several topics such as Classification, Classical Statistical Methods, Modern Statistical Techniques, Machine Learning of Rules and Trees, Neural Networks
Methods for Comparison, Review of Previous Empirical Comparisons, Dataset Descriptions and Results, Analysis of Results, Knowledge Representation, and Learning to Control Dynamical Systems
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Ellis Horwood
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homepages.inf.ed.ac.uk
The book covers the basic machine vision techniques such as template matching, segmentation, classification, edge detection, etc...
R. Nevatia
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markwatson.com
This book shows how to implement some AI techniques in java such as Search, Reasoning, Semantic Web, Expert Systems, Genetic Algorithms, Neural Networks, Machine Learning with Weka, Statistical Natural Language Processing, and Information Gathering....
Mark Watson
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4
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www.cs.ualberta.ca
"Reinforcement learning is learning what to do how to map situations to actions so as to maximize a numerical reward signal. The learner is not told which actions to take, as in most forms of machine learning, but instead must discover which actions yield the most reward by trying them....
Richard S. Sutton, Andrew G. Barto
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1
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aima.cs.berkeley.edu
"Artificial Intelligence (AI) is a big field, and this is a big book. We have tried to explore the full breadth of the field, which encompasses logic, probability, and continuous mathematics; perception, reasoning, learning, and action; and everything from microelectronic devices to robotic planetary explorers....
Stuart Russell and Peter Norvig
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1
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cswww.essex.ac.uk
"Constraint satisfaction is a general problem in which the goal is to find values for a set of variables that will satisfy a given set of constraints. It is the core of many applications in artificial intelligence, and has found its application in many areas, such as planning and scheduling....
Edward Tsang
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1
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