Sentiment Analysis with BERT extension by Redfield

This workflow demonstrates how to do sentiment analysis with BERT extension for Knime by Redfield. The dataset used here consists of the first 10000 reviews in the IMDB Movie Reviews dataset (http://ai.stanford.edu/~amaas/data/sentiment/) from "Learning Word Vectors for Sentiment Analysis" by Maas et al. Required Python packages (need to be available in your TensorFlow 2 Python environment): bert==2.2.0 bert-for-tf2==0.14.4 Keras-Preprocessing==1.1.2 numpy==1.19.1 pandas==0.23.4 pyarrow==0.11.1 tensorboard==2.2.2 tensorboard-plugin-wit==1.7.0 tensorflow==2.2.0 tensorflow-estimator==2.2.0 tensorflow-hub==0.8.0 tokenizers==0.7.0 tqdm==4.48.0 transformers==3.0.2


This is a companion discussion topic for the original entry at https://kni.me/w/IJy_hc39ojre0G6Z