So far, we have constructed network layers and parameters to define the model configuration. Now it's time to train the model and see the results. We can then check whether any of the previously-defined model configuration can be altered to obtain optimal results. Be sure to run the training instance multiple times before making any conclusions from the very first training session. We need to observe a consistent output to ensure stable performance.

In this recipe, we train our LSTM neural network against the loaded time series data.