t-SNE Supercharged

t-SNE is the very popular algorithm to extremely reduce the dimensionality of your data in order to visually present it. It is capable of mapping hundreds of dimensions to just 2 while preserving important data relationships, that is, when closer samples in the original space are closer in the reduced space. t-SNE works quite well for small and moderately sized real-world datasets and does not require much tuning of its hyperparameters. In other words, if you’ve got less than 100,000 points, you will apply that magic black box thing and get a beautiful scatter plot in return.