Machine learning: 3. Dimension reduction

Dimension reduction #

Labs and exercises #

1.	Clustering and neural network embeddings
2.	\(k\)-means cluster centers
3.	Operator norms
4.	SVD
5.	Stealing a production model
6.	Faces and dimension reduction
7.	The data manifold
8.	Unfolding the data manifold