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What is the purpose of Sequence Length parameter in RNN (specifically on PyTorch)?

The RNN receives as input a batch of sequences of characters. The output of the RNN is a tensor with sequences of character predictions, of just the same size of the input tensor. The number of ...
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RNN/LSTM timeseries, with fixed attributes per run

You can create a sort of encoder-decoder network with two different inputs. ...
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Training data for anomaly detection using LSTM Autoencoder

I will try to clarify the point as best as I can. Ideally a model for anomaly détection should be trained with typical data, so that atypical data (anomalies) stand out. However in practice this may ...
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Why does averaging word embedding vectors (exctracted from the NN embedding layer) work to represent sentences?

A simple, intuitive explanation- think of each latent dimension as a measure of some (very abstract) quality or property of a word. The value a word's coordinate has in that dimension describes how ...
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Should I remove the trend from timeseries when using DeepAR

Yes, you should. The main reason you should do this is because when data is trending up/down, it's more difficult to sample the useful data when training the model as the data is changing constantly, ...
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