Mohammed M., Khan M.B., Bashier E.B.M. Machine Learning. Algorithms and Applications

CRC Press, 2017. — 274.This book focuses on the supervised and unsupervised machine learning methods. The main objective of this book is to introduce these methods in a simple and practical way, so that they can be understood even by beginners to get benefit from them.
In each chapter, we discuss the algorithms through which the chapter methods work, and implement the algorithms in MatLAB. We chose MatLAB to be the main programming language of the book because it is simple and widely used among scientists; at the same time, it supports the machine learning methods through its statistics toolbox.Introduction to Machine Learning
I Supervised Learning Algorithms
Decision Trees
Rule-Based Classifiers
Naïve Bayesian Classification
The k-Nearest Neighbors Classifiers
Neural Networks
Linear Discriminant Analysis
Support Vector Machine
II Unsupervised Learning Algorithms
k-Means Clustering
Gaussian Mixture Model
Hidden Markov Model
Principal Component Analysis
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