dataaspirant-handle-overfitting-deep-learning-EarlyStopping-model.py

## EarlyStopping with keras
from tensorflow.keras.callbacks import EarlyStopping

model = Sequential()
model.add(Dense(128, input_dim=2, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
model.compile(loss='binary_crossentropy',
              optimizer='adam',
              metrics=['accuracy'])

callback= EarlyStopping(monitor='val_loss')
history = model.fit(x_train, y_train,
                    validation_data=(x_test, y_test),
                    epochs=2000,callbacks=[callback])