This is a basic number classifier which learns number from various writing styles.
we use the data set mnist which avaible in tensorflow itself.
then we load the data in x,y_train and x,y_test.
the use a simple nueral net model which has:-
1)One Flatten layer
2)Three fully connected layers with a (relu) activation function.
3)Output layer with a (sigmoid) activation function.
the model was fitted by using optimizer='adam' and loss_function='sparse_categorical_crossentropy'and Epoch=10.
then saved it by using model.save("name_of_model.model")
this model has
acc=0.9929
loss=0.0212
val_acc=0.9772
val_loss=0.0531
For more info checkout my code at ("https://github.com/rustombhesania/number_classifier").
Thnx for watching.
the reference was taken from ("https://pythonprogramming.net/introduction-deep-learning-python-tensorflow-keras/")