Nixtla's Open Source Time Series Ecosystem.

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Hey <@U05B45BNKT2>,

Assuming that you encoded text information from the series, that remains static you can feed it to NeuralForecast through stat_exog_list

Consider 3d embeddings that you put in a pandas stat_df with columns ‘e1’, ‘e2’, ‘e3’
You send stat_exog_list=[ ‘e1’, ‘e2’, ‘e3’]

Thanks alot, sorry for being a newbie and making you reply all the time

Basically, I have just started a phd in wind speed forecasting so was trying different things. I wanted to know that if I want to do research would it be better to stick with nixtla or use pytorch? Or a combination of both wherever applicable. Thanks

NeuralForecast is built on top of Pytorch and Pytorch Lightning

If you want to do your own models research, it is a good starting point