Amazon SageMaker Canvas gives enterprise analysts with a visible interface to resolve enterprise issues utilizing machine studying (ML) with out writing a single line of code. Since we launched SageMaker Canvas in 2021, many customers have requested us for an enhanced, seamless collaboration expertise that allows information scientists to share educated fashions with their enterprise analysts with a number of easy clicks.
Right this moment, I’m excited to announce which you can now convey ML fashions constructed wherever into SageMaker Canvas and generate predictions.
New – Deliver Your Personal Mannequin into SageMaker Canvas
As a knowledge scientist or ML practitioner, now you can seamlessly share fashions constructed wherever, inside or outdoors Amazon SageMaker, with your enterprise groups. This removes the heavy lifting on your engineering groups to construct a separate software or person interface to share ML fashions and collaborate between the completely different elements of your group. As a enterprise analyst, now you can leverage ML fashions shared by your information scientists inside minutes to generate predictions.
Let me present you ways this works in observe!
On this instance, I share an ML mannequin that has been educated to determine prospects which are probably vulnerable to churning with my advertising analyst. First, I register the mannequin within the SageMaker mannequin registry. SageMaker mannequin registry helps you to catalog fashions and handle mannequin variations. I create a mannequin group known as
2022-customer-churn-model-group after which choose Create mannequin model to register my mannequin.
To register your mannequin, present the situation of the inference picture in Amazon ECR, in addition to the situation of your
mannequin.tar.gz file in Amazon S3. You can even add mannequin endpoint suggestions and extra mannequin info. When you’ve registered your mannequin, choose the mannequin model and choose Share.
Now you can select the SageMaker Canvas person profile(s) throughout the identical SageMaker area you need to share your mannequin with. Then, present extra mannequin particulars, resembling details about coaching and validation datasets, the ML downside kind, and mannequin output info. You can even add a notice for the SageMaker Canvas customers you share the mannequin with.
Equally, now you can additionally share fashions educated in SageMaker Autopilot and fashions accessible in SageMaker JumpStart with SageMaker Canvas customers.
The enterprise analysts will obtain an in-app notification in SageMaker Canvas mannequin has been shared with them, together with any notes you added.
My advertising analyst can now open, analyze, and begin utilizing the mannequin to generate ML predictions in SageMaker Canvas.
Choose Batch prediction to generate ML predictions for a whole dataset or Single prediction to create predictions for a single enter. You possibly can obtain the leads to a .csv file.
New – Improved Mannequin Sharing and Collaboration from SageMaker Canvas with SageMaker Studio Customers
We additionally improved the sharing and collaboration capabilities from SageMaker Canvas with information science and ML groups. As a enterprise analyst, now you can choose which SageMaker Studio person profile(s) you need to share your standard-build fashions with.
Your information scientists or ML practitioners will obtain the same in-app notification in SageMaker Studio as soon as a mannequin has been shared with them, together with any notes from you. Along with simply reviewing the mannequin, SageMaker Studio customers can now additionally, if wanted, replace the info transformations in SageMaker Knowledge Wrangler, retrain the mannequin in SageMaker Autopilot, and share again the up to date mannequin. SageMaker Studio customers may suggest an alternate mannequin from the checklist of fashions in SageMaker Autopilot.
As soon as SageMaker Studio customers share again a mannequin, you obtain one other notification in SageMaker Canvas that an up to date mannequin has been shared again with you. This collaboration between enterprise analysts and information scientists will assist democratize ML throughout organizations by bringing transparency to automated choices, constructing belief, and accelerating ML deployments.
The improved, seamless collaboration capabilities for Amazon SageMaker Canvas, together with the power to convey your ML fashions constructed wherever, can be found at the moment in all AWS Areas the place SageMaker Canvas is obtainable with no adjustments to the prevailing SageMaker Canvas pricing.
Begin collaborating and convey your ML mannequin to Amazon SageMaker Canvas at the moment!