Hands-On Deep Learning Algorithms with Python

Computing loss

Compute the loss using cross entropy. We know that the cross-entropy loss is given as follows:

Here, is the actual label and is the predicted label. Thus, the cross-entropy loss is implemented as follows:

cross_entropy = -tf.reduce_sum(y*tf.log(YHat))

Minimize the loss using the Adam optimizer:

optimizer = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)

Calculate the accuracy:

predicted_digit = tf.argmax(y_hat, 1)actual_digit ...