April 24, 2024
Voiced by Polly

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 just a few easy clicks.

At this time, I’m excited to announce that you would be able to now convey ML fashions constructed wherever 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 wherever, inside or exterior Amazon SageMaker, with your corporation groups. This removes the heavy lifting to 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 information scientists inside minutes to generate predictions.

Let me present you ways this works in follow!

On this instance, I share an ML mannequin that has been skilled to determine prospects which might be probably susceptible to churning with my advertising 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 referred to as 2022-customer-churn-model-group after which choose Create mannequin model to register my mannequin.

Amazon SageMaker Model Registry

To register your mannequin, present the placement of the inference picture in Amazon ECR, in addition to the placement of your mannequin.tar.gz file in Amazon S3. You too can add mannequin endpoint suggestions and extra mannequin info. When you’ve registered your mannequin, choose the mannequin model and choose Share.

Amazon SageMaker Studio - Share models from model registry with SageMaker Canvas users

Now you can select the SageMaker Canvas person profile(s) throughout the similar SageMaker area you need to share your mannequin with. Then, present extra mannequin particulars, resembling details about coaching and validation datasets, the ML downside sort, and mannequin output info. You too can add a observe for the SageMaker Canvas customers you share the mannequin with.

Amazon SageMaker Studio - Share a model from Model Registry with SageMaker Canvas users

Equally, now you can additionally share fashions skilled in SageMaker Autopilot and fashions out there 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.

Amazon SageMaker Canvas - Received model from SageMaker Studio

My advertising analyst can now open, analyze, and begin utilizing the mannequin to generate ML predictions in SageMaker Canvas.

Amazon SageMaker Canvas - Imported model from SageMaker Studio

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 ends in a .csv file.

Amazon SageMaker Canvas - Generate Predictions

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 an identical 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 also advocate 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 selections, constructing belief, and accelerating ML deployments.

Now Accessible
The improved, seamless collaboration capabilities for Amazon SageMaker Canvas, together with the power to convey your ML fashions constructed wherever, can be found at this time in all AWS Areas the place SageMaker Canvas is offered with no modifications to the prevailing SageMaker Canvas pricing.

Begin collaborating and produce your ML mannequin to Amazon SageMaker Canvas at this time!

— Antje