Keras callback'leri

Keras ile Deep Learning'e Giriş

Miguel Esteban

Data Scientist & Founder

Callback nedir?

Keras ile Deep Learning'e Giriş

Keras'ta callback'ler

Keras ile Deep Learning'e Giriş

Eksik kaldığınız bir callback

# Training a model and saving its history
history = model.fit(X_train, y_train,
                    epochs=100,
                    metrics=['accuracy'])

print(history.history['loss'])
[0.6753975939750672, ..., 0.3155936544282096]
print(history.history['accuracy'])
[0.7030952412741525, ..., 0.8604761900220599]
Keras ile Deep Learning'e Giriş

Eksik kaldığınız bir callback

# Training a model and saving its history
history = model.fit(X_train, y_train,
                    epochs=100,
                    validation_data=(X_test, y_test),
                    metrics=['accuracy'])        

print(history.history['val_loss'])
[0.7753975939750672, ..., 0.4155936544282096]
print(history.history['val_accuracy'])
[0.6030952412741525, ..., 0.7604761900220599]
Keras ile Deep Learning'e Giriş

Geçmiş grafikleri

# Plot train vs test accuracy per epoch
plt.figure()

# Use the history metrics plt.plot(history.history['accuracy']) plt.plot(history.history['val_accuracy'])
# Make it pretty plt.title('Model accuracy') plt.ylabel('Accuracy') plt.xlabel('Epoch') plt.legend(['Train', 'Test']) plt.show()

Keras ile Deep Learning'e Giriş

Geçmiş grafikleri

Keras ile Deep Learning'e Giriş

Erken durdurma

# Import early stopping from keras callbacks
from tensorflow.keras.callbacks import EarlyStopping

# Instantiate an early stopping callback early_stopping = EarlyStopping(monitor='val_loss', patience=5)
# Train your model with the callback model.fit(X_train, y_train, epochs=100, validation_data=(X_test, y_test), callbacks = [early_stopping])
Keras ile Deep Learning'e Giriş

Model kaydı (checkpoint)

# Import model checkpoint from keras callbacks
from keras.callbacks import ModelCheckpoint

# Instantiate a model checkpoint callback model_save = ModelCheckpoint('best_model.hdf5', save_best_only=True)
# Train your model with the callback model.fit(X_train, y_train, epochs=100, validation_data=(X_test, y_test), callbacks = [model_save])
Keras ile Deep Learning'e Giriş

Hadi pratik yapalım!

Keras ile Deep Learning'e Giriş

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