Code:
import tensorflow
from tensorflow import keras
from tensorflow.keras import Sequential
from tensorflow.keras.layers import Dense, Flatten
import ssl
ssl._create_default_https_context = ssl._create_unverified_context
(X_train,Y_train), (X_test,Y_test) = keras.datasets.mnist.load_data()
print(X_train.shape)
print(Y_train.shape)
print(X_test.shape)
print(Y_test.shape)
X_train[0].shape
import matplotlib.pyplot as plt
plt.imshow(X_train[0])
plt.show()
X_train = X_train/255
X_test = X_test/255
model = Sequential()
model.add(Flatten(input_shape=(28,28)))
model.add(Dense(128,activation='relu'))
model.add(Dense(10,activation='softmax'))
model.summary()
model.compile(loss='sparse_categorical_crossentropy',optimizer='Adam',metrics=['accuracy'])
model.fit(X_train,Y_train,epochs=10,validation_split=0.2)
model.evaluate(X_test,Y_test)[1]*100
