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Sentiment classifier for Sindhi text (dual TF-IDF + LinearSVC) — v2: 91.7% acc / 0.918 macro F1 on a fully human-labeled 4,420-sentence dataset. Includes a transparent writeup of why accuracy dropped from v1's biased eval set.
Python project for scraping Daily Sobh news data and training machine learning (Logistic Regression, Decision Tree, Random Forest, SVM) and LSTM models to predict news topics from headlines. Developed for the DSA course at SMIU. Disclaimer: Educational purposes only. Not affiliated with Daily Sobh. Contributor: Furqan Hun.