Unsupervised Clustering, Expectation Maximization, Gaussian Mixture Model, K Means Clustering, Tensorflow Probability.
solve our clustering problem. Once we have p(x | θ), we can estimate the probability P(cluster id |x) i.e (probability of ith cluster given the data point x) by Bayes theorem. Now let us define the probability distribution of cluster ids as well, now we assume we have K clusters hence cluster ids