--> 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 :
● Tensorflow
● PIL
● 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 :