Gatsby Unit PhD Modules Coursework
As part of the MSc in Machine Learning programme at UCL, I had the opportunity to take two modules at the Gatsby Unit aimed at their PhD students. Each of the modules had a substantial piece of coursework, which are linked below:
1st Module: Probabilistic and Unsupervised Learning
Topics: Text decryption with MCMC, EM algorithm, Gibbs Sampling for LDA, Model Selection, Optimisation.
2nd Module: Approximate Inference and Learning in Probabilistic Models
Topics: Graphical Models, Gaussian Processes, Variational Inference, Expectation Propagation, Belief Propagation.
