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What's your go-to model that generally performs well with little tuning?



If you have short time-series with low variance, noise and outliers, strong prior knowledge, or limited resources to train and maintain a model, I would stick with simpler traditional models.

If DL is a good fit for your use-case, then I tend to like transformers or combining CNNs with recurrent models (e.g., BiGRU, GRU, BiLSTM, LSTM) and optional attention.




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