Python Deep Learning Projects

Fitting the model

Finally, we need to fit the model:

# fit the model on batches with real-time data augmentationhistory = model.fit_generator(train_datagen.flow(X_train, y_train, batch_size=128), steps_per_epoch=len(X_train) / 128, epochs=10, validation_data=(train_datagen.flow(X_val, y_val)))

The following is the output of the preceding code:

The following is the output at the end of the code's execution:

Figure 8.34: Metrics printed out during the training of the deep convolution classifier on augmented data