In this chapter, we looked at how to use a built-in machine learning tool called Comprehend in AWS. We briefly discussed the field of NLP and provided an introduction to its subfields, such as NER and sentiment analysis. We also examined how to create a custom document classifier in Comprehend using the dashboard it provides. Moreover, we explored how to access Comprehend's APIs using the boto3 package in Python.
These tools are fascinating as they will help you to create complex machine learning models quickly and start applying them in your applications. A data scientist who has cursory knowledge in the field of NLP can now train sophisticated machine learning models and use them to make optimal decisions. However, the question that most data scientists face is whether the pricing provided by such tools is more economical than building algorithms in-house using...
