Introduction to Machine Learning Paperback – 25 January 2015 by Alpaydin Ethem

Contents - 

1.   Introduction
2    Supervised learning
3.   Bayesian decision theory
4.   Parametric methods
5.   Multivariate methods
6.   Dimensionality reduction
7.   Clustering
8.   Nonparametric methods
9.   Decision trees
10. Linear discrimination
11. Multiplayer perceptrons
12. Local models;
13. Kernel machines;
14. Graphical models
15. Hidden Markov models
16. Bayesian estimation;
17. Combining multiple learners;
18. Reinforcement learning;