Topic Modelling is an information retrieval technique to identify topics in a large corpus of text documents. This talk will introduce you to the visualizations which have recently been added to gensim to aid the process of training topic models and analyze their results for downstream NLP applications.
Topic Modelling is a great way to infer topics in a large corpus of text documents but analyzing them could become difficult without any visualization. The purpose of this talk is to introduce the visualizations that aids the process of training topic models and analyze their results. I’ll give a brief introduction to Topic Models before moving to visualizations.
I’ll demonstrate the steps to train the LDA model in gensim and create the following visualizations using the trained model and how to interpret them: