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Amazon SageMaker Canvas supplies 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 information scientists to share skilled fashions with their enterprise analysts with a number of easy clicks.
As we speak, I’m excited to announce which you could now deliver ML fashions constructed anyplace into SageMaker Canvas and generate predictions.
New – Convey Your Personal Mannequin into SageMaker Canvas
As a knowledge scientist or ML practitioner, now you can seamlessly share fashions constructed anyplace, inside or exterior Amazon SageMaker, with what you are promoting groups. This removes the heavy lifting in your engineering groups to construct a separate software or person interface to share ML fashions and collaborate between the totally different components 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 apply!
On this instance, I share an ML mannequin that has been skilled to determine clients which can be doubtlessly prone to churning with my advertising and marketing analyst. First, I register the mannequin within the SageMaker mannequin registry. SageMaker mannequin registry allows 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 too 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, reminiscent of details about coaching and validation datasets, the ML drawback sort, and mannequin output info. You can too 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 accessible 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 and marketing 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 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 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 information scientists will assist democratize ML throughout organizations by bringing transparency to automated selections, constructing belief, and accelerating ML deployments.
Now Accessible
The improved, seamless collaboration capabilities for Amazon SageMaker Canvas, together with the flexibility to deliver your ML fashions constructed anyplace, can be found as we speak in all AWS Areas the place SageMaker Canvas is on the market with no adjustments to the present SageMaker Canvas pricing.
Begin collaborating and produce your ML mannequin to Amazon SageMaker Canvas as we speak!
— Antje
