Groups
t-SNE and UMAP are nonlinear dimensionality-reduction methods that preserve local neighborhoods to make high-dimensional data visible in 2D or 3D.
Metric learning is about automatically learning a distance function so that similar items are close and dissimilar items are far in a feature space.