Oct 10- Hy guys, I am trying to use this code to predict the evolution of a signal that has a frequency that is a function of time. The idea is that i generate some samples (6000) and after performing the usual preprocessing passages (scaling, dividing into testing and training data) I try to use a window of 100 prior datapoints and no features to predict the following single datapoint.
Even if my network is simple it does not seem able to get a meaningful prediction and this can be easily seen by running the fitting, that shows that the testing and training losses do not decrease.
What am I doing wrong?
I am posting a link to my notebook, hosted on github
Write me if you can’t access it, it’s my first time using git.

  
      gist.github.com
  
  
    https://gist.github.com/enrolivi/77d34ed242ee789daa7ea318bae515a2 1
lstm-pytorch.ipynb
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      "name": "LSTM-pytorch.ipynb",
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      "authorship_tag": "ABX9TyMFY4S/PeigTFIGVHfB3kFq",
      "include_colab_link": true
    },
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