Part 15: Step by Step Guide to Master NLP – Topic Modelling using NMF

This article was published as a part of the Data Science Blogathon

Introduction

This article is part of an ongoing blog series on Natural Language Processing (NLP). In the previous article, we discussed all the basic concepts related to Topic modelling. Now, from this article, we will start our journey towards learning the different techniques to implement Topic modelling. In this article, we will be discussing a very basic technique of topic modelling named Non-negative Matrix Factorization (NMF).

So, In this article, we will deep dive into the concepts of NMF and also discuss the mathematics behind this technique in a detailed manner.

This is part-15 of the blog series on the Step by Step Guide to Natural Language Processing.

 

Table of Contents

1. What is Non-negative Matrix Factorization (NMF)?

2. General Case of NMF

3. Maths Behind NMF

4. Objective Function in NMF

5. Some heuristics to initialize the matrix W and H

6. NMF in Action or real-life example

 

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