Analysis into a credit risk dataset and application of several supervised learning models to predict the binary variable on default status
-
Updated
Feb 21, 2026 - Jupyter Notebook
Analysis into a credit risk dataset and application of several supervised learning models to predict the binary variable on default status
Three classification models trained to predict failures of machines on the production line.
End-to-end ML pipeline for imbalanced tabular data using Neural Networks and LightGBM with PR-AUC optimization, calibration, and stacking.
Add a description, image, and links to the pr-auc topic page so that developers can more easily learn about it.
To associate your repository with the pr-auc topic, visit your repo's landing page and select "manage topics."