LGDiMaggio
Leveraging AI for Next-Gen Machine Diagnosis and Maintenance | Assistant Professor @polito
Politecnico di Torino @politoTurin
Pinned Repositories
CWRU-bearing-fault-classification-ML
A machine learning project for classifying bearing faults using the CWRU dataset, with models built using Python and various ML techniques such as cross-validation, PCA, tSNE, SVM, XGBoost.
Explainable-AI-for-Machine-Fault-Diagnosis
This project uses Explainable AI (XAI) to interpret machine learning models for diagnosing faults in industrial bearings. By applying SVM and kNN models and leveraging SHAP values, it enhances the transparency and reliability of machine learning in industrial condition monitoring.
LGDiMaggio
LGDiMaggio's Repositories
LGDiMaggio/Explainable-AI-for-Machine-Fault-Diagnosis
This project uses Explainable AI (XAI) to interpret machine learning models for diagnosing faults in industrial bearings. By applying SVM and kNN models and leveraging SHAP values, it enhances the transparency and reliability of machine learning in industrial condition monitoring.
LGDiMaggio/CWRU-bearing-fault-classification-ML
A machine learning project for classifying bearing faults using the CWRU dataset, with models built using Python and various ML techniques such as cross-validation, PCA, tSNE, SVM, XGBoost.
LGDiMaggio/LGDiMaggio