Amazon SageMaker
Integrate your Amazon SageMaker Inference Endpoint effortlessly with Datasaur. Utilize Datasaur's ML Assisted Labeling to access and leverage your deployed Amazon SageMaker Inference Endpoint for data labeling.
Setup Datasaur ML Assisted Extension
Please ensure you have access to our ML Assisted Extension with Amazon SageMaker as a provider.
Create a custom project for Row Labelling
Click “Manage Extension” on your right bar.
Pop Up Manage Extension will appear, and you can enable the Datasaur ML Assisted.
Datasaur ML Assisted is now enabled and select Amazon SageMaker as Provider
Setup Role in AWS Identity and Access Management (IAM)
Before we start to create Role in the IAM Page, please create these policies first for your permissions when creating a new Role.
Go to your IAM Page, navigate to the Policies section, and then create a new policy.
You can download the examples below.
Now you can continue to create a new Role with the policy.
Go to the IAM Page and navigate to the Roles section
Click on "Create Roles" then select "AWS Account" as the role type and insert the Account ID and External ID. These values are automatically generated within the Datasaur ML Assisted and can be copied and pasted into the AWS platform.
After finishing the first step, you can see the "Add permissions" step and search the policy you created before. Add them to the permissions.
Provide a role name and click “Create role” and you can check the trusted policies config below
The role will be created successfully.
View your role and copy the Role ARN.
Paste this information into the ML-Assisted Labeling extension.
Navigate to the Amazon SageMaker page and retrieve the Endpoint ARN. Copy the obtained Endpoint ARN and paste it into the extension.
Start Prediction
After setting up the above options, simply click "Predict Labels" to start predicting and obtaining labels from your Amazon SageMaker endpoint.
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