(Python) Extreme events model inspired from Uber article
Model inspired from the following article https://eng.uber.com/neural-networks/
Its aim is to used time series features to forecast extreme events
(Python) Extreme events model inspired from Uber article
(Python) Extreme events model inspired from Uber article
Model inspired from the following article https://eng.uber.com/neural-networks/
Its aim is to used time series features to forecast extreme events
Hi gimpgael,
I'm working on an event forecasting project, and would like to clarify my doubt. According to my understanding of the Uber paper the LSTM autoencoder is used for feature extraction, then what's the point of having those functions which are also doing feature extraction ?
Thanks!
Hi I wanted to try running this code but I dont see any main functions to generate the results. I am an absolute beginner and I was wondering if you could add those codes so that I can directly run this code on my system?
Would you please build the algorithm for predicting the future 365 days of data with this model?
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