BERT to the rescue!

In this post, I want to show how to apply BERT to a simple text classification problem. I assume that you're more or less familiar with what BERT is on a high level, and focus more on the practical side by showing you how to utilize it in your work. Roughly speaking, BERT is a model that knows to represent text. You give it some sequence as an input, it then looks left and right several times and produces a vector representation for each word as the output. In their paper, the authors describe two ways to work with BERT, one as with "feature extraction" mechanism.