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shippedOct 2024 — Mar 2025

EUNO: ML-Based Mood Tracker (Graduation Project)

ML-powered mood tracking app predicting mood-streak continuations from historical emotional data. Random Forest classifier (~87% accuracy, ROC AUC 0.95) trained with SMOTE for class imbalance.

Completed

The work

  • ML-powered mood tracking app predicting mood-streak continuations from historical emotional data.
  • Random Forest classifier (~87% accuracy, ROC AUC 0.95) trained with SMOTE for class imbalance.
  • FastAPI backend serves real-time predictions; Flutter app collects data and visualizes predictions.
  • Built with Jaser Quteshat under Dr.
  • Ahmad Barghash.