Collection of lightweight data applications

Sentiment Classifier

Write a movie review! Click outside the box to generate the sentiment.

How it works

The texts are first represented by 10k TFIDF word scores that represent word affinity. These features are then feeded in a standard dense neural network, with 6 layers and gradually fewer neurons. Finally, the network outputs a single chance for being a positive review, between 0 and 1.

This notebook contains this pipeline from preprocessing movie reviews to building a sentiment classifier model. It classifies 88% validation reviews correctly - but does not do equally well on short reviews.