Technical requirements

To follow along with the examples and exercises in this chapter on text preprocessing, you will need a working knowledge of a programming language such as Python, as well as some familiarity with NLP concepts. You will also need to have certain libraries installed, such as Natural Language Toolkit (NLTK), spaCy, and scikit-learn. These libraries provide powerful tools for text preprocessing and feature extraction. It is recommended that you have access to a Jupyter Notebook environment or another interactive coding environment to facilitate experimentation and exploration. Additionally, having a sample dataset to work with can help you understand the various techniques and their effects on text data.

Text normalization is the process of transforming text into a standard form to ensure consistency and reduce variations. Different techniques are used for normalizing text, including lowercasing, removing special characters, spell checking, and stemming or lemmatization...