Building the document classification workflow

In this section, we will get right down to action and start executing the tasks to build our solution. But first, there are prerequisites we will have to take care of.

Setting up to solve the use case

If you have not done so in the previous chapters, you will first have to create an Amazon SageMaker Jupyter notebook and set up Identity and Access Management (IAM) permissions for that notebook role to access the AWS services we will use in this notebook. After that, you will need to clone the GitHub repository (https://github.com/PacktPublishing/Natural-Language-Processing-with-AWS-AI-Services), go to the Chapter 15 folder, and open the chapter15 classify documents with human in the loop.ipynb notebook.

Now, let's move to the next section to show you how you can set up the libraries and upload training data to Amazon S3 using this notebook.

Setting up and uploading sample documents to Amazon S3

In this step, we will follow...