Remove app auth sign-up
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Secure Amazon SageMaker Studio presigned URLs Part 2: Private API with JWT authentication

AWS Machine Learning

The process includes the following steps: In the Amazon Cognito user pool, first set up a user with the name matching their Studio user profile and register Studio as the app client in the user pool. Pre-Signed URL Lambda Auth Policy. Pre-Signed URL Lambda Auth Policy. Deploy the solution.

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Use AWS AI and ML services to foster accessibility and inclusion of people with a visual or communication impairment

AWS Machine Learning

After deploying the web app, you will be able to access the following features: Live transcription and text to speech – The app transcribes conversations and speeches for you in real time using Amazon Transcribe, an automatic speech recognition service. Type what you want to say, and the app translates and says it for you.

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Use a pre-signed URL to provide your business analysts with secure access to Amazon SageMaker Canvas

AWS Machine Learning

The Canvas app. IAM as method of authentication is a strict requirement, because the API CreatePresignedDomainURL requires the IAM authentication method, and it won’t work with AWS Single Sign-On authentication for your domain. For Auth type , select NONE. You can now set up the permissions to run SageMaker calls.

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Accelerate time to insight with Amazon SageMaker Data Wrangler and the power of Apache Hive

AWS Machine Learning

Option 2: No-Auth In the No-Auth authentication CloudFormation template, we use a standard EMR cluster with no authentication enabled. LDAP No Auth Choose Next. Clean up If your work with Data Wrangler is complete, the following steps will help you delete the resources created to avoid incurring additional fees.

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