Simple Works: Building Effective Text Classifiers with TF-IDF and Naive Bayes

Text classification is ubiquitous in modern applications—from spam detection to ticket routing—yet most engineers assume it requires complex deep learning. This article proves otherwise: TF-IDF and Naive Bayes can achieve 84% accuracy on real datasets with just 10 lines of Python, making them a practical, interpretable, and GPU-free alternative for production systems. Whether you're resource-constrained or prioritizing model transparency, this demonstrates that complexity isn't always necessary for effective text classification.