Machine Learning II

In this course, students learn about machine learning and the data preparation workflow. The machine learning tasks covered include multivariate non-linear non-parametric regression, supervised classification, unsupervised classification and deep learning. For these machine learning tasks, it is shown how to assess the quality of the machine learning models and perform error estimation and feature engineering. All material covered is reinforced through hands-on experiences using state-of-the-art tools to design and execute data mining processes. Class examples come from Matlab, Python and R.

LEARN

Multivariate Non-Linear Non-Parametric Regression, Supervised Classification, Unsupervised Classification, Deep Learning

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