Unsupervised Clustering, Expectation Maximization, Gaussian Mixture Model, K Means Clustering, Tensorflow Probability.
supervision they are already given. So from the above example, we see, if we have labels available it is very easy, to calculate parameters by using analytical formula. But here in the unsupervised setting, we don't have initial labels, we randomly initialize all parameters, and then try to