Tutorial: Using Amazon ML to Predict Responses to a Marketing Offer
With Amazon Machine Learning (Amazon ML), you can build and train predictive models and host your applications in a scalable cloud solution. In this tutorial, we show you how to use the Amazon ML console to create a datasource, build a machine learning (ML) model, and use the model to generate predictions that you can use in your applications.
Our sample exercise shows how to identify potential customers for a targeted marketing campaign, but you can apply the same principles to create and use a variety of ML models. To complete the sample exercise, you will use publicly available banking and marketing datasets from the University of California at Irvine (UCI) Machine Learning Repository. These datasets contain general information about customers, and information about how they responded to previous marketing contacts. You will use this data to identify which customers are most likely to subscribe to your new product, a bank term deposit, also know as a certificate of deposit (CD).
To perform the tutorial, you need to have an AWS account. If you don't have an AWS account, see Setting Up Amazon Machine Learning.