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Use AWS PrivateLink to set up private access to Amazon Bedrock

AWS Machine Learning

Lambda makes a call to proprietary RDS database and augments the prompt query context (for example, adding product information) and invokes the Amazon Bedrock API with the augmented query request. As a next step, try the solution out in your account and share your feedback. You’re redirected to the IAM console.

APIs 125
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On Being an Accountable Customer Service Leader

Customer Service Life

This exercise reminded me of the time when we started this blog back in 2012. And furthermore, the team I was managing expected me to lead by example and show them the way they were to treat customers. Interact with customers out on the contact center floor, in full view of your team, being an example to them. History lesson.

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Build a multilingual automatic translation pipeline with Amazon Translate Active Custom Translation

AWS Machine Learning

It features interactive Jupyter notebooks with self-contained code in PyTorch, JAX, TensorFlow, and MXNet, as well as real-world examples, exposition figures, and math. ACT allows you to customize translation output on the fly by providing tailored translation examples in the form of parallel data.

APIs 77
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Automate and implement version control for Amazon Kendra FAQs

AWS Machine Learning

13, 2012-03-25T12:30:10+01:00 How many free clinics are there in Mountain View Missouri?, 7, 2012-03-25T12:30:10+01:00 Deploy the solution The CloudFormation templates that create the resources used by this solution can found in the GitHub repository. For example, demo-desc-hello world.json. Do you have feedback about this post?

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Get to production-grade data faster by using new built-in interfaces with Amazon SageMaker Ground Truth Plus

AWS Machine Learning

Specify the following trust relationship for the role: { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Principal": { "Service": "sagemaker-ground-truth-plus.amazonaws.com" }, "Action": "sts:AssumeRole" } ] }. Enter a name (for example, GTPlusExecutionRole ) and optionally a description of the role. Choose Next.

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Integrate HyperPod clusters with Active Directory for seamless multi-user login

AWS Machine Learning

For Directory DNS name , enter your preferred directory DNS name (for example, hyperpod.abc123.com Configure an NLB with the following parameters: For Load balancer name , enter a name (for example, nlb-ds ). ssh/config using the following example. Leave your feedback on this solution in the comments section. Choose Next.

Scripts 70
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Schedule your notebooks from any JupyterLab environment using the Amazon SageMaker JupyterLab extension

AWS Machine Learning

Examples of such use cases include scaling up a feature engineering job that was previously tested on a small sample dataset on a small notebook instance, running nightly reports to gain insights into business metrics, and retraining ML models on a schedule as new data becomes available.

Scripts 77