Poornima Singh completed Predictive Maintenance: Industrial ML for Fault Detection

Built a compact rolling-bearing fault detector end to end: engineered time-domain features, trained a shallow decision tree on training bearings only, and evaluated it on a held-out set with catch-rate and false-alarm rate. The candidate also wrote a maintenance memo that justified an alarm threshold using explicit cost trade-offs and translated the result into plain language for non-experts.

• Leakage-Aware Model Training
• Held-Out Evaluation
• Cost-Based Operational Decision-Making