Summary

We have just scratched the surface with what we can do with written text with this use case – the possibilities are truly endless! With just a few steps, by leveraging the advanced AI capabilities offered by services such as Amazon Textract, and the serverless scalable visualization offered by Amazon QuickSight, we were able to create powerful visuals from content scribbled on a piece of paper.

We began by creating the SageMaker Jupyter notebook instance we needed for this solution, cloned the GitHub repository for this chapter, created an S3 bucket, and executed the steps in the notebook to format the QuickSight S3 manifest file. Then, we used Amazon Textract and the Textract Response Parser library to read the contents of the handwritten receipts before creating CSV files that were uploaded to the S3 bucket. We concluded the notebook after executing these steps and then logged into the AWS Management Console and registered to use Amazon QuickSight.

In QuickSight...