Chapter 3: Machine Learning

Patrick BangertArtificial Intelligence Team, Samsung SDS America, San Jose, CA, United Statesalgorithmica technologies GmbH, Küchlerstrasse 7, Bad Nauheim, Germany


The field of machine learning is introduced at a conceptual level. Ideas such as supervised and unsupervised as well as regression and classification are explained. The tradeoff between bias, variance, and model complexity is discussed as a central guiding idea of learning. Various types of model that machine learning can produce are introduced such as the neural network (feed-forward and recurrent), support vector machine, random forest, self-organizing map, and Bayesian network. Training a model is discussed next with its main ideas of splitting ...

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