This repository is contains example code to train machine learning models for text classification as part of the Conversation AI project.

• experiments/ contains the ML training framework.
• annotator-models/ contains a Dawid-Skene implementation for modelling rater quality to produce better annotations.
• attention-tutorial/ contains an introductory ipython notebook for RNNs with attention, as presented at Devoxx talk "Tensorflow, deep learning and modern RNN architectures, without a PhD by Martin Gorner"
• kaggle-classification/ early experiments with Keras and Estimator for training on the Jigsaw Toxicity Kaggle competition. Will be superceeded by experiments/ shortly.
• model_evaluation/ contains utilities to use a model deployed on cloud MLE, and some notebooks to illustrate typical evaluation metrics.

This repository contains example code to help experiment with models to improve conversations; it is not an official Google product.