Machine Learning, Markov Chains, Statistics, NLP, Fun.
Markov Chain. Source We can express the probability of going from state a to state b as a matrix component, where the whole matrix characterizes our Markov chain process, corresponding to the digraph’s adjacency matrix. Source Then, if we represent the current state as a one-hot encoding, we can