Matrix_learning_different dimensions


I have a database of representative matrices that all have the same number of columns but do not have the same number of rows.
1) What is the best way to apply supervised learning with a database of matrix samples.
2) How can we avoid the normalization or compression of data

The deep learning can solve these problems ?

Best regards