This project tackles defect prediction in semiconductor manufacturing using sensor data from wafer production processes.

End-to-end ML pipeline for semiconductor wafer defect prediction with SHAP explainability

A portfolio of semiconductor data analysis projects, including wafer defect classification and yield prediction

AI + Edge AI + LLM system for wafer yield prediction, defect inspection, and intelligent semiconductor manufacturing analytics.

This assignment focuses on detecting scratch-related defects in semiconductor wafer maps using tabular data. The task includes feature engineering, handling class imbalance, model training and evaluation, and generating final predictions on a held-out test set for submission.