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Is it possible to train recurrent neural networks with multiple outputs in dataiku? How would one add beam search?

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In the current version of the visual deep learning (see doc: https://doc.dataiku.com/dss/latest/machine-learning/deep-learning/index.html) of Dataiku DSS, you can only train models with one output. We support using RNN, and you can find examples in the code samples.

If you wish to train a model with multiple outputs, you can use a Python recipe. You will need to write the preprocessing and the architecture of the model. You will also need to write your implementation fo the beam search.

Best regards,

Nicolas Servel

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