
Natural Language Processing with AWS AI Services
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In this section, we will introduce and walk through the Amazon Textract APIs for real-time analysis and batch processing of documents. We will show these APIs in action using Amazon SageMaker Jupyter notebooks. For this section, you will need to create an Amazon SageMaker Jupyter notebook and set up IAM permissions for that notebook role to access Amazon Textract. After that you will need to clone the notebook from our GitHub repository (https://github.com/PacktPublishing/Natural-Language-Processing-with-AWS-AI-Services), download the sample images, create an Amazon S3 (https://aws.amazon.com/s3/) bucket, upload these images to the S3 bucket, and then refer to this location in the notebook for processing.
Let's get started: