Build machine learning models for classification, regression, dimension reduction, or clustering, using advanced algorithms including deep learning, tree-based methods, and logistic regression.
Optimize model performance with hyperparameter optimisation, boosting, bagging, stacking, or building complex ensembles.
Validate models by applying performance metrics including Accuracy, R2, AUC, and ROC. Perform cross validation to guarantee model stability.
Explain machine learning models with LIME, Shap/Shapley values. Understand model predictions with the interactive partial dependence/ICE plot.
Make predictions using validated models directly, or with industry leading PMML, including on Apache Spark.