The workflow builds, trains, and saves an RNN with an LSTM layer to generate new fictive fairy tales. The brown nodes define the network structure. The "Pre-Processing and Encoding" part of the workflow reads the fairy tales, index-encodes them, and creates semi-overlapping sequences. The Keras Network Learner node trains the network using the index-encoded fairy tales. Finally, the trained network is converted into a TensorFlow model, and saved to a file.
Used extensions & nodes
Created with KNIME Analytics Platform version 4.3.0
By using or downloading the workflow, you agree to our terms and conditions.
Discussions are currently not available, please try again later.