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Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning

Central model registry – Amazon SageMaker Model Registry is set up in a separate AWS account to track model versions generated across the dev and prod environments. Approve the model in SageMaker Model Registry in the central model registry account. Create a pull request to merge the code into the main branch of the GitHub repository.

Scripts 122
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Build Streamlit apps in Amazon SageMaker Studio

AWS Machine Learning

As long as a user has access to the AWS account, Studio domain ID, and user profile, they can access the link. Next the script will install packages iproute and jq , which will be used in the following step. Next the script will install packages iproute and jq , which will be used in the following step. sh setup.sh sh setup.sh

Scripts 92
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Generate training data and cost-effectively train categorical models with Amazon Bedrock

AWS Machine Learning

The following is the code to parse the output: # This python script parses LLM output into a comma separated list with the SupportID, Category, Reason # Command line is python parse_llm_putput.py Enterprise Support Manager at AWS leading the technical and strategic advisory team of TAM builders for automotive and manufacturing customers.

Education 107
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Schedule your notebooks from any JupyterLab environment using the Amazon SageMaker JupyterLab extension

AWS Machine Learning

Migrating from interactive development on notebooks to batch jobs required you to copy code snippets from the notebook into a script, package the script with all its dependencies into a container, and schedule the container to run. In the following section, we show an example of using initialization scripts to install packages.

Scripts 93
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Set up Amazon SageMaker Studio with Jupyter Lab 3 using the AWS CDK

AWS Machine Learning

You have permissions to create and deploy AWS CDK and AWS CloudFormation resources as defined in the scripts outlined in the post. AWS CDK scripts. Review the resources the AWS CDK creates in your AWS account and select yes when prompted to deploy the stack. The AWS CDK is installed. Clone the GitHub repository.

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Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

AWS Machine Learning

Healthcare organizations must navigate strict compliance regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States, while implementing FL solutions. FedML Octopus is the industrial-grade platform of cross-silo FL for cross-organization and cross-account training.

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Top Contact Solutions Expert: Team Member Spotlight

Quality Contact Solutions

Julie came to QCS with 20 years of call center industry experience, including 17 years in Account Management and Client Services. Other Articles You Might Find Interesting: How to Write an Outbound Telemarketing Script. Meet Julie Kramme. Julie is an outsourced telemarketing and call center operations expert.