Data Science, Machine Learning, Artificial Intelligence, Technology, Cybersecurity.
loss='categorical_crossentropy', metrics=['accuracy']) # Train the model and capture history history_non_dp = model_non_dp.fit(train_data, train_labels, epochs=5, batch_size=32, validation_data=(test_data, test_labels)) # Plot training vs validation accuracy plt.figure(figsize=(12, 6))