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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 introduced SageMaker Canvas in 2021, many customers have requested us for an enhanced, seamless collaboration expertise that allows knowledge scientists to share educated fashions with their enterprise analysts with just a few easy clicks.
Today, I’m excited to announce you can now carry ML fashions constructed anyplace into SageMaker Canvas and generate predictions.
New – Bring Your Own Model 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 corporation groups. This removes the heavy lifting on your engineering groups to construct a separate instrument 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 knowledge scientists inside minutes to generate predictions.
Let me present you ways this works in observe!
In this instance, I share an ML mannequin that has been educated to establish clients which can be doubtlessly vulnerable to churning with my advertising and marketing analyst. First, I register the mannequin within the SageMaker mannequin registry. SageMaker mannequin registry enables 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 may add mannequin endpoint suggestions and extra mannequin data. Once you’ve registered your mannequin, choose the mannequin model and choose Share.
You can now select the SageMaker Canvas person profile(s) inside the identical SageMaker area you wish to share your mannequin with. Then, present further mannequin particulars, corresponding to details about coaching and validation datasets, the ML drawback sort, and mannequin output data. You may add a notice for the SageMaker Canvas customers you share the mannequin with.
Similarly, now you can additionally share fashions educated in SageMaker Autopilot and fashions out there in SageMaker LeapStart 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 and marketing analyst can now open, analyze, and begin utilizing the mannequin to generate ML predictions in SageMaker Canvas.
Select Batch prediction to generate ML predictions for a whole dataset or Single prediction to create predictions for a single enter. You can obtain the ends in a .csv file.
New – Improved Model Sharing and Collaboration from SageMaker Canvas with SageMaker Studio Users
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 person 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. In addition to simply reviewing the mannequin, SageMaker Studio customers can now additionally, if wanted, replace the information transformations in SageMaker Data 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 record of fashions in SageMaker Autopilot.
Once 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 Available
The enhanced, seamless collaboration capabilities for Amazon SageMaker Canvas, together with the flexibility to carry your ML fashions constructed anyplace, can be found immediately in all AWS Regions the place SageMaker Canvas is obtainable with no adjustments to the prevailing SageMaker Canvas pricing.
Start collaborating and produce your ML mannequin to Amazon SageMaker Canvas immediately!
— Antje