ABSTRACT
There are various types of situations one encounters while working with text data. This chapter lists some common scenarios surrounding data and model building along with practical tips for navigating through the challenges. Once a model is built and tested in isolation, it needs to be deployed. This chapter summarizes what model deployment entails, commonly used tools, and an example of deploying a model using Amazon Sagemaker. Other than the data and model, some other factors play an important role in producing NLP solutions in the real world, such as model explainability. This chapter shares some final thoughts and good practices.
