Lecture
Nonlinear Dimension Reduction Methods
Description
This lecture covers the concept of dimension reduction beyond PCA, focusing on methods that aim to preserve neighborhoods while reducing the dimension. The instructor explains techniques such as t-SNE and UMAP, which transform data by building neighbor graphs and projecting them onto lower-dimensional spaces. Various applications of these methods, including single-cell RNA sequencing analysis and animal behavior studies, are also discussed.
Official source
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