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I don't have an issue for it yet so this is just to collect some links without having to edit the readme:
- [How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls](ht…
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https://arxiv.org/abs/1910.13051
This approach feels very unique compared to the majority of forecasting models which are either using Transformers or DNNs while also being much faster.
It's for…
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I was hoping someone could clear up the use of `from_dataset()` in the demand forecasting example using TFT.
```
training = TimeSeriesDataSet(
data[lambda x: x.date < training_cutoff],
t…
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Prophet: forecasting at scale
- https://peerj.com/preprints/3190/ | https://peerj.com/preprints/3190.pdf
- https://facebook.github.io/prophet/
Link to the Stan code
- https://github.com/facebo…
yebai updated
5 months ago
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Hi Team,
I am referring to the below two scenarios:
**Scenario1**:https://www.katacoda.com/courses/openshift/ai-machine-learning/prometheus-api-client
**Scenario2:** https://learn.openshift.com/a…
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62695: 1 EC Strip
Below stores have MAD above 170:
J718032,G135801, C750108,G135802,G135813,G135804
C75108: Variations are not captured in the forecast:
 where they introduced a new model (called Cyclic Boosting). It's a type of generalized additive model using a cyclic coordinate descent op…
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Dear Maintainer,
I hope this message finds you well.
I am writing to you regarding your outstanding work on the tsai project, which has been instrumental in maintaining state-of-the-art models f…