Source: aws.amazon.com
New – Bring ML Models Built Anywhere into Amazon SageMaker Canvas and Gener
https://aws.amazon.com/polly/ https://aws.amazon.com/sagemaker/canvas provides business analysts with a visual interface to solve business problems using machine learning (ML) without writing a single line of code. Since we https://aws.amazon.com/blogs/aws/announcing-amazon-sagemaker-canvas-a-visual-no-code-machine-learning-capability-for-business-analysts/, many users have asked us for an enhanced, seamless collaboration experience that enables data scientists to share trained models with their business analysts with a few simple clicks.
New – Bring Your Own Model into SageMaker Canvas As a data scientist or ML practitioner, you can now seamlessly share models built anywhere, within or outside Amazon SageMaker, with your business teams. This removes the heavy lifting for your engineering teams to build a separate tool or user interface to share ML models and collaborate between the different parts of your organization. As a business analyst, you can now leverage ML models shared by your data scientists within minutes to generate predictions.
New – Bring Your Own Model into SageMaker Canvas As a data scientist or ML practitioner, you can now seamlessly share models built anywhere, within or outside Amazon SageMaker, with your business teams. This removes the heavy lifting for your engineering teams to build a separate tool or user interface to share ML models and collaborate between the different parts of your organization. As a business analyst, you can now leverage ML models shared by your data scientists within minutes to generate predictions.
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