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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

Policy 3 – Attach AWSLambda_FullAccess , which is an AWS managed policy that grants full access to Lambda, Lambda console features, and other related AWS services.

Scripts 99
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Contact Center Trends 2021: The CX Watershed

Fonolo

As the focus of contact center turns to creating value rather than reducing expenses, KPIs like customer satisfaction and service level will become increasingly favored over metrics like Average Handling Time. FCR is the Most Important Metric. 2016: 50% of Global 1000 companies will have stored customer-sensitive data in the cloud.

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Machine learning with decentralized training data using federated learning on Amazon SageMaker

AWS Machine Learning

The notebook instance client starts a SageMaker training job that runs a custom script to trigger the instantiation of the Flower client, which deserializes and reads the server configuration, triggers the training job, and sends the parameters response. script and a utils.py The client.py

Scripts 71
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Securing MLflow in AWS: Fine-grained access control with AWS native services

AWS Machine Learning

The MLflow Python SDK provides a convenient way to log metrics, runs, and artifacts, and it interfaces with the API resources hosted under the namespace /api/. You can use this script add_users_and_groups.py mlflow/runs/search/", "arn:aws:execute-api: : : / /POST/api/2.0/mlflow/experiments/search", large', framework_version='1.0-1',

APIs 70