Best Practices for NLP Classification in TensorFlow 2.0

When I first started working with Deep Learning, I went through Coursera and fast.ai I started asking questions like "How do I develop a data pipeline for a model?" and "How do I implement state-of-the-art research?". The post covers the development a deep learning model in TensorFlow 2.0 from the ingestion of data all the way to the point where deep learning determines the emotion of a Yelp review (positive or negative). After reading this post, you will also be able to use Huggingface's Transformers library [1] in order to create state of the art models using a new technique called transfer learning and using a "model backbone" from Google (BERT [2]) that was pre-trained on Wikipedia. One of the keys to success in Deep Learning is to iterate quickly.