Machine Learning, Data Science, Algorithms, Dimensionality Reduction, Cheatsheet.
should try t-SNE first. If you have a lot of data, autoencoders can help you to find very complex latent representations. If you don’t have a lot of data, try PCA for linear dimensionality reduction and manifold learning algorithms (LLE, Isomap, and others) for non-linear dimensionality reduction.