7 Must Read Books To Learn 'Machine Learning' - OpenXcell G.R. Jenkin

It offers sufficient background material on linear algebra, probability, optimization, conditional random fields, L1 regularization, deep learning and more. In the introductory chapter the book lays out different kinds of problems that can be solved by machine learning and describes the types of methods that can be used to solve them. The book progresses on to discuss these and related issues in the chapters ahead. The book uses the language of graphical models to specify models in a concise and intuitive way. Overviews of real-world applications of various techniques are provided. MATLAB and GNU octave code which implements the algorithms provided in the book can be feely downloaded from the book's website. It is not an easy read but an authoritative book intended to be used as a text book.