Machine Learning Model Training — Classification & Regression

I will train, evaluate, and deliver a machine learning model for your classification or regression use case — covering algorithm selection, hyperparameter tuning with cross-validation, evaluation with appropriate metrics, feature importance analysis, and a deployment-ready model export. A properly trained and evaluated ML model is not one that achieves high training accuracy — it is one that generalises correctly to unseen data, handles class imbalance appropriately, and comes with honest performance documentation your stakeholders can rely on when making decisions based on model outputs.

The model build covers preprocessing pipeline, algorithm selection and justification, cross-validated hyperparameter tuning, held-out test set evaluation, confusion matrix or residual analysis, feature importance plot, and model export in pickle or ONNX format with an inference script.