Building a Question-Answering System from Scratch-- Part 1

As my Masters is coming to an end, I wanted to work on an interesting NLP project where I can use all the techniques(not exactly) I have learned at USF. With the help of my professors and discussions with the batch mates, I decided to build a question-answering model from scratch. I am using the Stanford Question Answering Dataset (SQuAD). The problem is pretty famous with all the big companies trying to jump up at the leaderboard and using advanced techniques like attention based RNN models to get the best accuracy. All the GitHub repositories that I found related to SQuAD by other people have also used RNNs. However, my goal is not to reach the state of the art accuracy but to learn different NLP concepts, implement them and explore more solutions.