@takotab, awsome job for being able to develop a fastai v2 version of the N-BEATS article.
In my repo, I included documentation that I generated using nbdev_buid_docs but I have some issues that prevent generating the css, js, images folders. I will post the issue in the nbev thread later.
A couple month ago, I played with Amazon Labs’ time series forecasting repo called GluonTS (maybe you are already familiar with. If it’s the case, please ignore the rest of the post). As everybody might guess, their implementation uses Amazon MXNet. I must say it’s quiet impressive what they have achieved. They implemented almost all the architecture that you can think of ( DeepFactor, DeepAR, DeepState, GP Forecaster, GP Var, LST Net, N-BEATS, NPTS, Prophet, R Forecast, seq2seq, Simple FeedForward, Transformer, Trivial, and WaveNet). I think it’s worth exploring it for those interested in time series forecasting.
They use their models for both univariate and multivariate timeseries (with millions of timeseries as they describe in some of their papers). They also leverage covariate information like day of week, month, year, or any other time series’ related information.