SageMakerAs an integration-first platform, we encourage you to leverage the best tools available at each step of the ML pipeline, and we’ve designed our platform to integrate seamlessly with upstream platforms.
If you’re using SageMaker Notebooks to train your models, you can deploy your code to Algorithmia straight from within your notebook, and we’ll take care of serving your model in production. To learn about several possible workflows, see our step-by-step guide to deploying models from SageMaker.
The following video walkthrough demonstrates deploying a scikit-learn model trained in SageMaker.
To learn more about model deployment on Algorithmia, see our Deployment Guides. Also, see our documentation on Connecting Your Data for more information on how to connect your algorithms to your data and model files.
If you’re new to Algorithmia and would like to learn more about our product and capabilities, please contact our sales team. We’d love to hear from you!