The individual machine learning services provided by AWS are incredibly powerful by themselves, but when used together, they are extraordinary. Chaining the services together can create truly magical experiences. However, the outputs and inputs of each of these services need to be coordinated because each service takes a varying amount of time based on the original input data. Step Functions are one way to keep track of all of these moving pieces.
In this lab, you will be modifying an existing pipeline to learn how to set up the coordination between the services. We will be using Lambda functions in the background to run the logic of our pipeline, but all of the Lambda functions are provided for you.
Learning Objectives
Successfully complete this lab by achieving the following learning objectives:
- Add Translation to the Pipeline
Modify the Polyglot-Pipeline to include Translation utilizing the existing Lambda functions on the account.
- Add Sentiment Analysis to the Pipeline
Modify the Polyglot-Pipeline to include Sentiment Analysis utilizing the existing Lambda functions on the account.
- Convert the Translated Text to Audio
Modify the Polyglot-Pipeline to convert the translated text to audio utilizing the existing Lambda functions on the account.
- Upload Audio and Test the Pipeline
Upload the audio files provided in Github to S3 and observe the results.
