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Topic 1 – Quantitative methods
Module 7 – Machine Learning
0:00 LOS: Introduction and learning outcome statements
7:25 LOS: Distinguish between supervised machine learning, unsupervised machine learning, and deep learning;
15:40 LOS: Describe overfitting and identify methods to address it;
20:54 LOS: Describe supervised machine learning algorithms – including penalized regression, support vector machine, k-nearest neighbor, classification and regression tree, ensemble learning, and random forest – and determine the problems for which they are best suited;
46:17 LOS: Describe unsupervised machine learning algorithms – including principal component analysis, K-means clustering, and hierarchical clustering – and determine the problems for which they are best suited;
56:09 LOS: Describe neural networks, deep learning nets, and reinforcement learning.

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