Implementing Deep Learning Methods and Feature Engineering for Text Data: FastText

Editor's note: This post is only one part of a far more thorough and in-depth original, found here, which covers much more than what is included here. The FastText model was first introduced by Facebook in 2016 as an extension and supposedly improvement of the vanilla Word2Vec model. Based on the original paper titled'Enriching Word Vectors with Subword Information' by Mikolov et al. which is an excellent read to gain an in-depth understanding of how this model works. Overall, FastText is a framework for learning word representations and also performing robust, fast and accurate text classification. The framework is open-sourced by Facebook on GitHub and claims to have the following.