--> DATASET:

This dataset is directly imported from keras library mnist.

ABOUT THE DATASET :

The training data has 60,000 images and 10,000 images for testing data and 28x28 pixels size.

--> METHODOLOGY :

Mainly the libraries used to implement this project are :

● Keras

model.predict() gives the prediction probability of each class for that data point and then the np.argmax() function is used to convert the prediction probabilities to class label.

--> OUTPUT :

The given output is :