This textbook covers the basics of pattern recognition and machine learning: basic theory and practices, classifiers, clustering, feature selection; as well as selected topics from the neural networks area: perceptrons, various classical neural network models, and deep learning neural networks.
The challenge in writing this textbook was to explain rigorous, intricate concepts and algorithms assuming minimal knowledge of mathematics. The students on this module would have completed a previous module ÒAlgorithm design with MATLABÓ. Hence, MATLAB examples are given at some places for the reader familiar with the language.
I deliberately use colloquial language, cartoons, and plenty of illustrations in an attempt to keep the students entertained throughout.