Implement a simple Pytorch classification for irregularly sampled time series
In order to test the workflow for irregularly sampled time series described here and here, we will use a simple Pytorch model (a simple MLP will do the job).
In the training step, the model will just take all the features provided in the sample files.
In the inference step, the model will have to format the input data in order to match the format used for the training.