Lead scoring model-training lab with Litestar, Pydantic v2, SHAP drivers, and DiCE counterfactual planning.
-
Updated
Jul 26, 2026 - Python
#
dice-ml
Here are 6 public repositories matching this topic...
TradingView strategy risk lab with model training, SHAP/DiCE explainability, Pydantic v2 validation, and Litestar API.
-
Updated
Jul 26, 2026 - Python
Prescriptive churn analytics with calibrated risk, uplift evidence, SHAP, counterfactuals, expected-value decisions, and a Next.js operations dashboard.
python xgboost prescriptive-analytics causal-inference treatment-effects churn-prediction uplift-modeling shap dowhy dice-ml
-
Updated
Jul 8, 2026 - Python
Explainable ML pipeline that clusters feasible counterfactuals and distills them into global interpretable rules using DiCE, SHAP, Polars, DuckDB, and scikit-learn.
machine-learning scikit-learn explainable-ai xai interpretable-machine-learning shap counterfactual-explanations duckdb polars dice-ml
-
Updated
Aug 9, 2026 - Python
Explainable, counterfactual-driven decision support system for credit risk prediction. Combines SHAP/LIME-based risk scoring with a counterfactual recommendation engine for rejected applicants, subgroup fairness auditing (demographic parity, equalized odds), and an interactive dashboard for applicants and loan officers.
-
Updated
Aug 3, 2026 - Python
This is a XAI-powered heart disease risk predictor using SHAP, LIME, PDP & DiCE counterfactuals-deployed on Streamlit
-
Updated
Jun 9, 2026 - Python
Improve this page
Add a description, image, and links to the dice-ml topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the dice-ml topic, visit your repo's landing page and select "manage topics."