NLP Essentials: Removing Stopwords and Performing Text Normalization using NLTK and spaCy in Python
Overview
- Learn how to remove stopwords and perform text normalization in Python – an essential Natural Language Processing (NLP) read
- We will explore the different methods to remove stopwords as well as talk about text normalization techniques like stemming and lemmatization
- Put your theory into practice by performing stopwords removal and text normalization in Python using the popular NLTK, spaCy and Gensim libraries
Introduction
Don’t you love how wonderfully diverse Natural Language Processing (NLP) is? Things we never imagined possible before are now just a few lines of code away. It’s delightful!
But working with text data brings its own box of challenges. Machines have an almighty struggle dealing with raw text. We need to perform certain steps, called preprocessing, before we can work with text data using NLP techniques.
Miss out on these steps, and we are in for a botched model. These are essential NLP techniques you need to incorporate in your code, your framework, and your project.
