Problem? Predict which medical devices require maintenance within the next 30 days to minimize downtime and ensure operational efficiency.

Steps taken: Simulated relevant device datasets, performed preprocessing and feature engineering, trained a Random Forest Classifier, and built an interactive Streamlit app with visualizations and filtering.

Result! Achieved accurate predictions with detailed performance metrics (accuracy, precision, recall, F1 score), enabling proactive maintenance through an interactive dashboard.