Unsupervised Machine Learning - Clustering
The difference between supervised and unsupervised machine learning is whether or not we, the scientist, are providing the machine with labeled data.
Unsupervised machine learning is where the scientist does not provide the machine with labeled data, and the machine is expected to derive structure from the data all on its own.
The main form of unsupervised machine learning is clustering. Within clustering, you have “flat” clustering or “hierarchical” clustering.
Flat clustering is where the scientist tells the machine how many categories to cluster the data into.
Hierarchical clustering is where the machine is allowed to decide how many clusters to create based on its own algorithms.
Scikit-learn (sklearn) is a popular machine learning module for the Python programming language.
The Scikit-learn module depends on Matplotlib, SciPy, and NumPy as well.