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: https://github.com/keras-team/keras/blob/master/examples/imdb_lstm.py 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.
This is a companion discussion topic for the original entry at https://kni.me/w/CUTYA0-niLdbXP5B