Data Driven Exploration: Unleashing Topic Modelling using Python

Abstract

Topic Modeling is a crucial technique in natural language processing that involves assigning topic labels to a set of text documents. The primary objective of topic modeling is to unveil the latent themes or subjects present within the textual data. This article serves as a comprehensive guide for individuals seeking to acquire knowledge on performing topic modeling using machine learning algorithms with the aid of Python. Through this article, readers will gain insights into the fundamental concepts of topic modeling, various machine learning techniques used in the process, and a step-by-step implementation using Python programming language. By the end of this article, readers will have a solid foundation in topic modeling and the necessary skills to explore and extract meaningful topics from their own text data.