kk7nc/Text_Classification resource

Health v2 · maintenance only

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1820 stars · 538 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A companion repository for the survey paper 'Text Classification Algorithms: A Survey', providing explanations and Python code for text classification techniques. It covers text preprocessing, feature extraction, and classical and deep learning classification algorithms.

Use cases

• learn text classification algorithms from a survey with code
• understand text preprocessing like tokenization and stop word removal
• compare classical classifiers like naive bayes and SVM for documents
• get started with deep learning models for text classification
• find reference implementations of word embedding and feature extraction
• study RNN and CNN approaches to document classification

When to choose

• you want a guided, paper-backed introduction to text classification methods
• you need example Python code for NLP preprocessing and classification baselines
• you are surveying classical and deep learning text classifiers before picking one

When to avoid

• you need a production-ready text classification library or service
• you want state-of-the-art transformer fine-tuning pipelines
• you need maintained, tested software rather than educational code snippets

Facets

learning-resource · maturity active

nlp machine-learning deep-learning machine-learning deep-learning tutorials python text-classification survey feature-extraction document-classification educational natural-language-processing

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