Building a feedforward neural network to recognize handwritten digits, version two

In the previous section, we built a very simple neural network with just an input and output layer. This simple neural network gave us an accuracy of 86%. Let's see if we can improve this accuracy further by building a neural network that is a little deeper than the previous version:

1. Let's do this on a new notebook. Loading the dataset and data pre-processing will be the same as in the previous section:

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.optimizers import SG
#loading and pre-processing 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&apos...