Assignments for COL776 - Probabilistic Grpahical Models 1A. Implementing the Bayes' Ball algorithm for finding independences in Bayesian networks (Implemented in C++) 1B. Implementing a simple CRF model for Optical Character Recognition (Python) 2A. Inference using clique tree message passing and cluster graph belief propagation in Markov Networks (Python) 2B. Inference using the Viterbi algorithm for Hidden Markov Models (Python) 3A. Inference using Gibbs sampling (MCMC) in Markov Networks (Python) 3B. POS tagging and Named Entity Recognition in Tweets (using MALLET)