Forecasting with LSTM using PyTorch
In this recipe, you will use the same train_model_pt
function from the previous Forecasting with an RNN using PyTorch recipe. The function trains the model, captures loss function scores, evaluates the model, makes a forecast using the test set, and finally, produces plots for further evaluation.
You will still need to define a new class for the LSTM model.
How to do it...
The following steps will use the energy consumption data. You can follow the same steps with the other datasets. The Jupyter notebook will include the steps and outputs for other datasets – air passengers and daily temperature: