This workflow shows how to train a simple neural network for text classification, in this case sentiment analysis. The used network learns a 128 dimensional word embedding followed by an LSTM.
This example is adapted from the following Keras example script:
In order to run the example, please make sure you have the following KNIME extensions installed:
* KNIME Deep Learning - Keras Integration (Labs)
You also need a local Python installation that includes Keras. Please refer to https://www.knime.com/deeplearning#keras for installation recommendations and further information.
To use this workflow in KNIME, download it from the below URL and open it in KNIME:Download Workflow
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