kk7nc/Text_Classification

Comprehensive resource covering end-to-end text classification pipelines with detailed implementations of preprocessing techniques (tokenization, stop word removal, stemming, lemmatization) and feature extraction methods including word embeddings and weighted word representations. The project provides practical Python code examples using NLTK and scikit-learn, demonstrating noise removal, spelling correction, and normalization strategies essential for preparing raw text data. Serves as both an educational survey and practical toolkit for implementing classical and modern text classification approaches.

1,832 stars. No commits in the last 6 months.