Description

Training machine learnings models and performing inference using third-party data from AWS Data Exchange.

Data is at the forefront of every decision that an organization makes. Leveraging the first party data that you own might not be enough to get deeper level insights that you are looking for. Augmenting your data with third-party data can further enhance the insights you can gain to help achieve your business outcomes. AWS Data Exchange makes it easy to find, subscribe to, and use third-party data in the cloud.

In this session, you will learn how to consume and build feature rich data pipelines using third-party data from AWS Data Exchange alongside AWS's machine learning services.

Presented by: AWS data exchange solution architects and AWS ML specialists

Agenda

• Hour 1: AWS Data Exchange Overview and Demos (including AWS Data Exchange for Amazon Redshift and APIs)
• Hour 2: Hand-on lab on how to subscribe to a data product and export data
• Hour 3: Train a computer vision model with Amazon SageMaker Image Classification
• Hour 4: Perform inference on a ML model using an Amazon SageMaker Notebook

Key takeaways

• Understand the important concepts of AWS Data Exchange
• Subscribe to third-party data on AWS Data Exchange and export data
• Learn how to train a computer vision model using data from AWS Data Exchange
• Learn how to perform inference on a ML model using data from AWS Data Exchange