Summary

In this chapter, we saw the journey of a deep learning project as it flows through an organization. We also learned about Google Colab notebooks to leverage GPUs for faster training. Additionally, we developed a Flask-based web service using Docker and deployed it to a cloud environment, hence enabling the stakeholders to obtain predictions for a given input.

This chapter concludes our efforts toward learning how to leverage deep learning techniques to solve problems in the domain of natural language processing. Almost every aspect discussed in this chapter and the previous ones is a topic of research and is being improved upon continuously. The only way to stay informed is to keep learning about the new and exciting ways to tackle problems. Some common ways to do so are by following discussions on social media, following the work of top researchers/deep learning practitioners, and being on the constant lookout for organizations that are doing cutting-edge work when it comes to this...