In the context of this lesson, what other unsupervised learning techniques are there?
In addition to clustering, there are several other techniques that can be used for unsupervised learning.
Artificial neural networks is another technique for performing unsupervised learning. This technique is inspired by the neural networks in real brains, like the ones that humans or animals have. These typically comprise of a graph-like interconnection of nodes, which represent neurons, that takes in input values, perform calculations along each connection, then produces some output values at the end.
Latent variable models are another technique used for unsupervised learning, which is a model that makes inferences based on some observable variables. This model can include a few different algorithms and approaches, such as principal component analysis and singular value decomposition.
One other technique for unsupervised learning is anomaly detection, which is used to find anomalies, or unexpected patterns or behaviors, in the datasets which differ greatly from the rest of the data.