Using a clever trick in leveraging static dictionaries in PL/Python, we can easily scale ML models from popular libraries like scikit-learn or XGBoost for data parallel problems. You can read the full blog that I published in the Pivotal Engineering Journal following the link below.
Building machine learning models at scale for data parallel problems on Pivotal’s MPP databases