unsupervised machine learning technique used to proudce a low-dimensional (2D) representation of a higher dimensional data set while preserving the topological structure of the data.
SOM is a thpe of artificial neural network but is trained using competitive learning rather than error-correction learning (e.g., backprop wih gradient descent)
competitive learning: form of unsupervised learning in ANN, in which nodes compete for the right to respond to a subset of the input data. a variant of hebbian learning, competitive learning works by increasing the specialization of each node in the network. it is well suited to finding clusters within data.
UMAP
general purpose manifold learning and dimension reduction algorithm (compatible wit scikit-learn)