Presented by: Carsten Eickhoff, PhD, assistant professor of medical and computer science at Brown University This talk introduces the basic components of machine learning systems and research papers and introduce the notion of casting inference problems in terms of features and labels. We discuss supervised classification and regression techniques as well as altogether unsupervised learning schemes. We look at reinforcement learning, model optimization and evaluation and close with a discussion of model generality and the curse of dimensionality.
Introduction to Machine Learning
Last modified: February 10, 2022
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