cover_type.py shows how to train a model on the forest cover type dataset using GPU acceleration. The forest cover type dataset has 581,012 rows and 54 features, making it time consuming to process. We compare the run-time and accuracy of the GPU and CPU histogram algorithms.
shap.ipynb demonstrates using GPU acceleration to compute SHAP values for feature importance.