blog_posts: 04233bd3d8
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id | createdDate | title | link | postExcerpt | featuredImageUrl | hash | contributors | modifiedDate | displayDate |
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blog-posts#34-10426 | 2019-11-26 23:02:48 | Save on inference costs by using Amazon SageMaker multi-model endpoints | https://aws.amazon.com/blogs/machine-learning/save-on-inference-costs-by-using-amazon-sagemaker-multi-model-endpoints/ | Businesses are increasingly developing per-user machine learning (ML) models instead of cohort or segment-based models. They train anywhere from hundreds to hundreds of thousands of custom models based on individual user data. For example, a music streaming service trains custom models based on each listener’s music history to personalize music recommendations. A taxi service trains [...] | https://d2908q01vomqb2.cloudfront.net/f1f836cb4ea6efb2a0b1b99f41ad8b103eff4b59/2019/11/26/multi-model-endpoints-1-300x152.gif | 04233bd3d8 | Mark Roy, Urvashi Chowdhary | 2020-01-06 23:09:23 | 26 Nov 2019 |
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