An ML engineer is training a time series aws video

Full Certification Question

An ML engineer is training a time series forecasting model using a recurrent neural network (RNN) to predict electricity demand for a utility company. The model is trained using stochastic gradient descent (SGD) as the optimizer. During training, the engineer notices the following: The training loss and validation loss remain high. The loss values oscillate, decreasing for a few epochs and then increasing again before repeating the cycle. The ML engineer needs to resolve this issue to stabilize the training process and improve model performance. What should the ML engineer do to improve the training process?