课程介绍

Learn how Dimensionality Reduction, a category of unsupervised machine learning techniques, is used to reduce the number of features in a dataset.

Dimension reduction can also be used to group similar variables together.

Learn the theory behind dimension reduction, and get some hands-on practice using Principal Components Analysis (PCA) and Exploratory Factor Analysis (EFA) on survey data using R.

课程大纲

考核标准

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课程内容不断迭代，成绩以当时的课程内容为准，一旦合格，可以申请证书。申请证书后，以结课处理，成绩不再改动