Get Started with the Implementation Guide

6 Steps  |  30 Minutes


With Amazon Machine Learning (Amazon ML), you can build and train predictive models and host your applications in a scalable cloud solution. In this project, you will use the visualization tools and wizards of Amazon ML to guide you through the process of creating a new machine learning (ML) model without having to learn complex ML algorithms and technology. To complete this project, you will download freely-available sample customer data and upload the data to an Amazon S3 bucket to create a datasource. You will then create an ML model from this datasource, from which you can then evaluate and adjust the ML model's performance, and then use it to generate predictions.

Get Started with the Implementation Guide

What you'll accomplish:

Create a datasource from Amazon S3, loading a CSV file of information about customers, and information about how they responded to marketing communications.

Build a machine learning model from the datasource.

Measure model accuracy and adjust score threshold accordingly.

Use your model to generate predictions that you can use in your applications. In this project, you can identify potential customers for a targeted marketing campaign.

What you'll need before starting:

An AWS Account: You will need an AWS account to begin building a machine learning model with Amazon ML. Sign up for AWS.

Skill level: No prior experience with machine learning is necessary to complete this project.

AWS Experience: Basic familiarity with Amazon S3 is suggested, but not required, to complete this project.

Monthly Billing Estimate:

The total cost of building this model, following the steps provided, is estimated to be $0.79. To see a breakdown of the services used and their associated costs, see Services Used and Costs.

Sign up for the on-demand webinar for an introduction to Amazon Machine Learning.

Sign up for the on-demand webinar to learn how an end-to-end smart application can be built in the AWS cloud.

Need more resources to get started with AWS? Visit the Getting Started Resource Center to learn more.