Machine learning and analytics

Workshop Overview

Title: Use an open-source Machine Learning model to analyze data from AWS Data Exchange.

Goal:

  1. Learn how data and ml products can be combined to extract insights.
  2. Learn how AWS Service Catalog portfolio can be set up to vend application containing multiple individual standard products.

Description:

In this workshop, you will learn how to use machine learning models and third-party datasets from AWS Marketplace to solve a machine learning problem. To set up the workshop environment itself, you will run a CloudFormation template that would set up an AWS Service Catalog portfolio containing following products:

  1. A dataset product - This product when deployed creates an S3 bucket and exports data of specific dataset and revision.
  2. An Amazon SageMaker Notebook instance product - This product when provisioned deploys ML model in form of an amazon SageMaker endpoint.
  3. An Amazon SageMaker Notebook instance product - This product when provisioned creates a notebook instance which you would use to perform an inference on the ML model

Once the portfolio has been set up, you will vend a single application product which internally creates the lab environment for you. You will open the notebook instance and do the lab.

Note: For this workshop, you are recommended to use the account you created using account factory. If you are an amazon employee, you cannot use an account part of an AWS Organization for doing this workshop.