9:40-16:40, May 17, 2020.
The goal of this day is to give an introduction to fundamental methods in dimensionality reduction.
In the morning, we will focus on linear method and principal component analysis. In the afternoon, we will give an overview of non-linear extension to PCA, such as kernel-PCA, t-SNE and auto-encoder.
Tutorial are available by mixing R and Python code. Some homework with correction is also provided if you want to get deeper insights on these methods on your own.
Zoom + Pad, remotely.