Machine Learning, Model Selection, Hyperparameter Tuning, Learning Curve, Cross Validation.
“production”. Since not all data is created equal, there is no general rule as to how the data should be split. A typical split is e.g. 50%/25%/25%. In any case, the validation set should be big enough to measure the difference in performance we want to be able to measure: If we care about a 0.1%