blog_posts: 26819b684b
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id | createdDate | title | link | postExcerpt | featuredImageUrl | hash | contributors | modifiedDate | displayDate |
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blog-posts#34-62427 | 2023-09-20 16:56:39 | Train and deploy ML models in a multicloud environment using Amazon SageMaker | https://aws.amazon.com/blogs/machine-learning/train-and-deploy-ml-models-in-a-multicloud-environment-using-amazon-sagemaker/ | In this post, we demonstrate one of the many options that you have to take advantage of AWS’s broadest and deepest set of AI/ML capabilities in a multicloud environment. We show how you can build and train an ML model in AWS and deploy the model in another platform. We train the model using Amazon SageMaker, store the model artifacts in Amazon Simple Storage Service (Amazon S3), and deploy and run the model in Azure. | https://d2908q01vomqb2.cloudfront.net/f1f836cb4ea6efb2a0b1b99f41ad8b103eff4b59/2023/09/20/train-and-deploy-ml-models-multicloud-300x150.jpg | 26819b684b | Raja Vaidyanathan, Amandeep Bajwa, Prema Iyer | 2023-09-20 16:56:39 | 20 Sep 2023 |
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