Building a deeper neural network

In this section, we will use the concepts we learned about in this chapter to build a deeper neural network to classify handwritten digits:

1. We will start with a new notebook and then load the required dependencies:

import numpy as np
np.random.seed(42)
import keras
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import Dropout
# new!
from
keras.layers.normalization
# new!
import
BatchNormalization
# new!
from keras import regularizers
# new! 
from keras.optimizers
import SGD

2. We will now load and pre-process the data:

(X_train,y_train),(X_test,y_test)= mnist.load_data()
X_train= X_train.reshape(60000,784).
astype('float32')
X_test= X_test.reshape(10000,784).astype('float32')
X_train/=255
X_test/=255
n_classes=10
y_train=keras.utils.to_categorical(y_train,n_classes...