NLP Module: Building Your Own Text Classifier — A Complete Guide to Custom Text Classification Text classification is one of the most practical applications of Natural Language Processing (NLP). It allows computers to read human language and automatically assign text to meaningful categories such as spam or not spam, positive or negative sentiment, technical or non-technical, sports or politics, or urgent and non-urgent. Modern NLP libraries make it possible to build sophisticated classifiers with pretrained transformers, but you do not always need a huge language model. In many real-world projects, a carefully designed custom text classifier using Python, text preprocessing, feature extraction, and machine learning can be fast, understandable, inexpensive, and surprisingly powerful. This guide explains how to build your own text classifier from the ground up. You will learn the complete workflow—from defining the classification problem and preparing a dataset to preprocessing t...
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