Sorry if I sound confused. I read that data to be fed to a machine are divided into training, validation and test data. Both training and validation data are used for developing the model. Test data is used only for testing the model and no tuning of the model is done using test data.
Why is there a need to separate out training and validation data since both sets of data are for developing/tuning the model? Why not keep things simple and combine both data sets into a single one?