Open it # Get the patterns of a layer in our network weights, biases = model_35.layers[1].get_weights()
Original toplevel document
TfC_02_classification-PART_2 tant: This time there is a problem with loss function. In case of categorical_crossentropy the labels have to be one-hot encoded In case of labels as integeres use SparseCategoricalCrossentropy <span># Get the patterns of a layer in our network weights, biases = model_35.layers[1].get_weights() <span>