In the past year, massive developments have been made in the natural language processing field. Improvements in areas such as question answering, machine translation, and sentiment analysis have opened up doors to utilize NLP more effectively than ever before.
In this tutorial we will perform a brief overview of the field of NLP and look at the Python libraries that allow us to utilize different techniques and models. We will start with simple, traditional approaches to NLP that will provide us baseline for our models. As we progress in the tutorial we will look at some more advanced concepts that can give quick boosts to model performance. We will end by introducing state-of-the-art language models and how we can incorporate them into applications that we build.