Statistisches Und Maschinelles Lernen: Gangige Verfahren Im UEberblick

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Supervised Learning: Grundlagen.- Lineare Algorithmen fur Regressionsprobleme.- Allgemeines zu Klassifikationsproblemen .- Lineare Methoden fur Klassifizierungsprobleme und SVMs.- Nichtparametrische Methoden und der naive Bayes-Klassifizierer.- Regressions- und Klassifikationsbaume; Bagging, Boosting und Random Forests.- Neuronale Netzwerke.- Reinforcement Learning / Bestarkendes Lernen.- Unsupervised Learning: Bestimmung von Reprasentanten.- Unsupervised Learning: Dimensionsreduktion.