1.A Course in Machine Learningby Hal Daumé III
2.A First Encounter with Machine Learningby Max Welling
3.An Introduction to Statistical Learning with Applications in Rby Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
4.Bayesian Reasoning and Machine Learningby David Barber
5.Gaussian Processes for Machine Learningby Carl Edward Rasmussen and Christopher K. I. Williams
6.How Are We To Know?by Nils J. Nilsson
7.Inductive Logic Programming Techniques and Applicationsby Nada Lavrac and Saso Dzeroski
8.Inductive Logic Programming: Techniques and Applicationsby Nada Lavrac, Saso Dzeroski
9.Information Theory, Inference, and Learning Algorithmsby David J.C. MacKay
10.Introduction to Machine Learningby Amnon Shashua
11.Introduction To Machine Learningby Nils J Nilsson
12.Machine Learningby Abdelhamid Mellouk and Abdennacer Chebira
13.Machine Learning plus Intelligent Optimizationby Roberto Battiti, Mauro Brunato
14.Machine Learning, Neural and Statistical Classificationby D. Michie, D.J. Spiegelhalter, C.C. Taylor
15.Practical Artificial Intelligence Programming in Javaby Mark Watson
16.Reinforcement Learningby C. Weber, M. Elshaw, N. M. Mayer
17.Reinforcement Learning: An Introductionby Richard S. Sutton and Andrew G. Barto
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