Statistical Foundations of Machine Learning
by Gianluca Bontempi, Souhaib Ben Taieb
Number of pages: 269
This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data. In particular, we focus on supervised learning problems, where the goal is to model the relation between a set of input variables, and one or more output variables, which are considered to be dependent on the inputs in some manner.
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