/Teaching-Machine-Reading-and-Comprehension

Primary LanguageJupyter NotebookMIT LicenseMIT

Teaching-Machine-Reading-and-Comprehension

1. Introduction

This project is focus on develop and implement a RNN model on Teaching Machine Reading and Comprehension.

This repository is for student projects githubs for e4040 2019 Fall.

I develop two model which are deeplstm and attentive reader.

Image of Yaktocat

2. Dataset

The original datasets can be downloaded from https://github.com/deepmind/rc-data or http://cs.nyu.edu/~kcho/DMQA/.

The other SciQ datasets I upload on github.

Word embeddings: glove.6B.zip: http://nlp.stanford.edu/data/glove.6B.zip

3. Prerequisites

  • Python >= 3.6
  • Tensorflow >= 1.13
  • Keras >= 2.30

4. Structure

  • utils: all help functions
  • model: all model funtions
  • result: all output figures, plots and flow charts
  • report: report paper
  • checkpoints: saver model data