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Build a cross-account MLOps workflow using the Amazon SageMaker model registry

AWS Machine Learning

When designing production CI/CD pipelines, AWS recommends leveraging multiple accounts to isolate resources, contain security threats and simplify billing-and data science pipelines are no different. Some things to note in the preceding architecture: Accounts follow a principle of least privilege to follow security best practices.

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The Case For the Anti-Script: A Multifactor Analysis of Script Adherence

Balto

“The anti-script doesn’t mean that you should wing it on every call… what anti-script means is, think about a physical paper script and an agent who is reading it off word for word… you’re taking the most powerful part of the human out of the human.” Share on Twitter. Share on Facebook.

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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 75
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Get smarter search results with the Amazon Kendra Intelligent Ranking and OpenSearch plugin

AWS Machine Learning

In this post, we show you how to get started with Amazon Kendra Intelligent Ranking for self-managed OpenSearch, and we provide a few examples that demonstrate the power and value of this feature. For this tutorial, you’ll need a bash terminal on Linux , Mac , or Windows Subsystem for Linux , and an AWS account. Prerequisites.

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

AWS Machine Learning

To achieve this multi-user environment, you can take advantage of Linux’s user and group mechanism and statically create multiple users on each instance through lifecycle scripts. Create a VPC, subnets, and a security group Follow the instructions in the Own Account section of the HyperPod workshop. Choose Next. Choose Next.

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AWS Transcribe With Nexmo Voice Using PHP

Nexmo

In this tutorial, we’ll use a Nexmo Voice number to create a callback script that interacts with a caller to prompt for a voice message. In this example the following are needed: PHP installed locally (version 7.3+ In this example the following are needed: PHP installed locally (version 7.3+ Nexmo account.

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Use the Amazon SageMaker and Salesforce Data Cloud integration to power your Salesforce apps with AI/ML

AWS Machine Learning

The following steps give an overview of how to use the new capabilities launched in SageMaker for Salesforce to enable the overall integration: Set up the Amazon SageMaker Studio domain and OAuth between Salesforce and the AWS account s. The following screenshot shows the example user profile for this post. Choose Create configuration.

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