Load dataset file, score features and split dataset into train and test.

Select machine learning model, train, run and save model performance.

Look into PCA, accuracy and loss curves, confusion matrix, and class precision to evaluate model performance.

Compare performance of scoring methods with combinations of machine learning models and hyperparameters.