Python Deep Learning Projects

Type conversion, centering, and scaling

Set the type to np.float32.

Important: One of the main reasons for doing this is that the weights will all be of the float type, and multiplication between floating numbers is much faster than between an integer and a float. So it's better to convert the input into the float type.

For centering, we subtract the dataset by 127.5. The values in the dataset will now range between -127.5 to 127.5.

For scaling, we divide the centered dataset by half of the maximum pixel value in the dataset, that is, 255/2. This will result in a dataset with values ranging between -1 and 1:

# Converting integer values to float types X_train = X_train.astype(np.float32)X_test = X_test.astype(np.float32)# Scaling and centering ...