Machine learning tasks classification
Some of the "tasks" (there are many more, for example anomaly detection; and people just love to invent their own tasks marginally different from before hoping to be the first to spawn a new subdomain...) can both be supervised or unsupervised.

Example:


PCA is unsupervised dimensionality reduction
Fishers' LDA is supervised dimensionality reduction


... and both predate any notion of machine learning, data science or data mining. These things are just rebranded into ML now, squeezed into a very narrow view that never was able to capture the essence of even clustering (beyond k-means, that seems to be the only method machine learners still understand and get taught, as the L2 nature of the method fits their world view well enough). I'd rather avoid making all this "machine learning" - it was not, and it doesn't fit well.