Deep Learning, Neural Networks, Keras, Python.
to decrease the loss (0.24) and improve accuracy (0.93) on the validation set on the last epoch. Making inferences on the test set We preprocess the previously unseen test set in a manner similar to the trainset and save it in scaled_test_samples. The corresponding labels are stored in test_labels