Amazon SageMaker Autopilot automatically builds, trains, and tunes the best machine learning models based on your data, while allowing you to maintain full control and visibility. Previously, the datasets were limited by a 10GB maximum. Now, you can now use SageMaker Autopilot to build machine learning models for regression and classification problem datasets with sizes up to 100 GB in all AWS supported regions. The default 100 GB service limit can be increased to support datasets larger than 100GB by filing a limit increase request in the AWS Support Center console.

Amazon SageMaker Autopilot eliminates the heavy lifting of building ML models by automatically exploring different solutions to find the best model. You can directly deploy the model to production with just one click, or iterate on the recommended solutions with Amazon SageMaker Studio for improved model quality.

For more details on input dataset limits and quotas, visit the Amazon SageMaker Autopilot Developer Guide. For a deeper dive, check out Amazon’s blog post and sample notebook previewing this feature launch. To get started with SageMaker Autopilot, see the product page or access SageMaker Autopilot within SageMaker Studio.

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