Amazon SageMaker
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Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
Product Overview
An implicit feedback matrix factorization model. Uses a classic matrix factorization approach, with latent vectors used to represent both users and items. Their dot product gives the predicted score for a user-item pair. The model is trained through negative sampling: for any known user-item pair, one or more items are randomly sampled to act as negatives (expressing a lack of preference by the user for the sampled item).
Key Data
| Version | |
| By | Outpace Systems |
| Categories | |
| Type | Algorithm |
| Fulfillment Methods | Amazon SageMaker
|
Usage Information
Fulfillment Methods
Amazon SageMaker
Additional Resources
End User License Agreement
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Support Information
Spotlight Implicit Factorization 0.9
see attached example notebookAWS Infrastructure
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Refund Policy
No refunds.