Guidance for first-time Amazon Personalize users
If you're a first-time user of Amazon Personalize, the following resources can help you get started.
Topics
Discovering Amazon Personalize with the Magic Movie Machine
The Magic Movie Machine is an interactive learning experience. It helps you discover Amazon Personalize features and learn more about generating
recommendations.
For a short introduction, see the video below. Then try the Magic Movie Machine
Navigating getting started materials in this guide
Review the following sections to get started with Amazon Personalize. For a checklist that provides lists of Amazon Personalize features, requirements, and data guidance, see Readiness checklist.
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How Amazon Personalize works – This section introduces the Amazon Personalize workflow and walks you through the steps to create personalized experiences for your users. This section also includes common Amazon Personalize terms and their definitions. Start with this section to make sure you have good understanding of Amazon Personalize workflows and terms before you start getting recommendations.
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Setting up Amazon Personalize – In this section you set up your AWS account, set up the required permissions to use Amazon Personalize, and set up the AWS CLI and the AWS SDKs to use and manage Amazon Personalize.
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Getting started tutorials – In this section you get started using Amazon Personalize with a simple movie dataset. Complete these tutorials to get hands-on experience with Amazon Personalize. You can choose to either get started with a Domain dataset group or a Custom dataset group:
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To get started creating a Domain dataset group, complete the Getting started prerequisites and then start the tutorials in Getting started with a Domain dataset group.
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To get started with a Custom dataset group, complete the Getting started prerequisites and then start the tutorials in Getting started with a Domain dataset group.
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After you complete the getting started exercise, you can start completing the Amazon Personalize workflow. For steps and links to documentation, see Amazon Personalize workflow.