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Amazon SageMaker Canvas offers enterprise analysts with a visible interface to unravel 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 knowledge scientists to share skilled fashions with their enterprise analysts with a couple of easy clicks.
At the moment, I’m excited to announce you can now carry ML fashions constructed anyplace 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 anyplace, inside or outdoors Amazon SageMaker, with your online business groups. This removes the heavy lifting on your engineering groups to construct a separate instrument or consumer interface to share ML fashions and collaborate between the totally different elements of your group. As a enterprise analyst, now you can leverage ML fashions shared by your knowledge scientists inside minutes to generate predictions.
Let me present you ways this works in apply!
On this instance, I share an ML mannequin that has been skilled to determine clients which are probably susceptible 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 referred to 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 too can add mannequin endpoint suggestions and extra mannequin data. When you’ve registered your mannequin, choose the mannequin model and choose Share.
Now you can select the SageMaker Canvas consumer profile(s) inside the similar SageMaker area you wish to share your mannequin with. Then, present further mannequin particulars, reminiscent of details about coaching and validation datasets, the ML downside sort, and mannequin output data. You too can add a word for the SageMaker Canvas customers you share the mannequin with.
Equally, now you can additionally share fashions skilled in SageMaker Autopilot and fashions obtainable in SageMaker JumpStart with SageMaker Canvas customers.
The enterprise analysts will obtain an in-app notification in SageMaker Canvas {that a} 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 complete dataset or Single prediction to create predictions for a single enter. You’ll be able to 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 knowledge science and ML groups. As a enterprise analyst, now you can choose which SageMaker Studio consumer profile(s) you wish to share your standard-build fashions with.
Your knowledge 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 information transformations in SageMaker Information Wrangler, retrain the mannequin in SageMaker Autopilot, and share again the up to date mannequin. SageMaker Studio customers may advocate an alternate mannequin from the listing 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 knowledge scientists will assist democratize ML throughout organizations by bringing transparency to automated choices, constructing belief, and accelerating ML deployments.
Now Accessible
The improved, seamless collaboration capabilities for Amazon SageMaker Canvas, together with the flexibility to carry your ML fashions constructed anyplace, can be found at present in all AWS Areas the place SageMaker Canvas is accessible with no adjustments to the prevailing SageMaker Canvas pricing.
Begin collaborating and produce your ML mannequin to Amazon SageMaker Canvas at present!
— Antje
