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Smart yield prediction and anomaly detection for semiconductor manufacturing processes using Machine learning models. This project focuses on analyzing sensor data and process parameters to procatively forecast final wafer yield, optimize fabrication control, and reduce waste in the semiconductor supply chain.

Machine Learning project for semiconductor yield prediction using preprocessing, SMOTE, and model comparison