Stemming in NLP

Introduction

Data preprocessing is a process of working with the raw data to make it suitable for use with a machine learning model. It is the first and most crucial step while creating a machine learning model. In the context of NLP, it turns the raw text data into a format that ML models can understand by reducing noise and ambiguity in the text data.

Some examples of preprocessing tasks in NLP include:

Parts-of-speech (POS) taggingStopword removalStemming

As can be seen, the first two poi...