In this type of split, the input data in randomly assigned to the test, train and validation set according to the given sizes.
The split is done without replacement, which means that the validation, test and training set doesn't contain the same data.
Random split is the simplest split strategy and is effective in most of the cases.
Only 13% of vision AI projects make it to production, with Hasty we boost that number to 100%.