Last updated on November 14, 2024
Amazon Personalize Cheat Sheet
- A fully managed machine learning service for building recommendation systems.
- Amazon Personalize allows you to train, build, and deploy recommendation models without an extensive machine learning experience.
- Offers batch and real-time recommendations.
Common Use Cases:
- Personalized product and content recommendations.
- Product rankings.
- Improves marketing communication through individualized push notifications and emails.
Concepts
- Amazon Personalize can provide recommendations based on real-time data, historical data, or a mix of both.
- Event trackers
- Records user interactions in real-time.
- Recipe
- Refers to the algorithm to be used in training a solution for a given use case.
- Available Recipes
- USER_PERSONALIZATION – optimized for personalized recommendation systems
- PERSONALIZED_RANKING – a hierarchical recurrent neural network (HRNN) for providing a list of best recommendations (e.g., ranking search results)
- RELATED_ITEMS – predicts item similar to a given item
Amazon Personalize Pricing
- Pay only for what you use.
- You are billed for data ingestion, training, and inference (recommendation)
Note: If you are studying for the AWS Certified Machine Learning Specialty exam, we highly recommend that you take our AWS Certified Machine Learning – Specialty Practice Exams and read our Machine Learning Specialty exam study guide.
Amazon Personalize Cheat Sheet References:
https://aws.amazon.com/personalize
https://aws.amazon.com/blogs/machine-learning/using-a-b-testing-to-measure-the-efficacy-of-recommendations-generated-by-amazon-personalize/
https://aws.amazon.com/blogs/machine-learning/amazon-personalize-can-now-create-up-to-50-better-recommendations-for-fast-changing-catalogs-of-new-products-and-fresh-content/
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