Deep Learning, Stock Prediction, Python, Financial Analysis, Programming.
build_model((X_train_scaled.shape[1],)) # Train the model history = model.fit(X_train_scaled, y_train, epochs=50, batch_size=32, validation_split=0.1, verbose=1) # Evaluate the model test_loss, test_accuracy = model.evaluate(X_test_scaled, y_test) print(f"Test accuracy: {test_accuracy}") #