Supervised & Unsupervised Approach to Topic Modelling in Python

This article will provide a high level intuition behind topic modelling and its associated applications. It will do a deep dive into various ways one can approach solving a problem which requires topic modelling and how you can solve those problems in both a supervised and unsupervised manner. I placed an emphasis on restructuring the data and initial problem such that the solution can be executed in a variety of methods. Topic modelling is a subsection of natural language processing (NLP) or text mining which aims to build models in order to parse various bodies of text with the goal of identifying topics mapped to the text. These models assist in identifying big picture topics associated with documents at scale.