NLP – Building a Question Answering Model

I recently completed a course on NLP through Deep Learning (CS224N) at Stanford and loved the experience. For my final project I worked on a question answering model built on Stanford Question Answering Dataset (SQuAD). In this blog, I want to cover the main building blocks of a question answering model. You can find the full code on my Github repo. Stanford Question Answering Dataset (SQuAD) is a new reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage.