In this program
- Proper scoring rules
- Calibration and fairness metrics
- Interpretability: SHAP
- LIME (overview)
- Statistical inference after model selection (intro)
Evaluation and deployment
Calibration and fairness metrics
Machine learning for statistics · STEM / applied
Topic
Calibration and fairness metrics
Graduate Machine learning for statistics — outline derived from course README sections and typical US statistics syllabi (OpenIntro / standard OER where applicable).