Along with the dataset, two tasks are proposed to evaluate machines'

This mostly includes tasks with multifaceted objectives, such as dialogue response generation, or tasks with hard-to-define goals, such as enhancing program readability.

Code for feature engineering Interpreter: Executes generated code T abular Prediction Model: Performs cross-validation.

On one hand, the knowledge learned from public data is implicitly transferred into the private model.