Training Latent Dirichlet Allocation: Gibbs Sampling - Part 2

This course teaches learners how to train a Latent Dirichlet Allocation (LDA) model using Gibbs sampling. The goal is to understand the properties of LDA and apply Gibbs sampling to effectively sort documents into topics. The teaching method involves a theoretical introduction, problem recap, exercise, explanation of Gibbs Sampling, and a conclusion. This course is intended for individuals interested in natural language processing, machine learning, and topic modeling techniques.