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Azure Machine learning Federated learning

Federated learning sampling introduction


Federated learning Steps

  • Create a workspace
  • Create a compute instance
  • or local workstation is also fine
  • there is bicep code to create the workspace and compute instance


  • Login into Azure CLI
az login --tenant <tenant-id>
az account set --name <subscription name>
  • create a reource group
az group create --name fltest --location eastus
  • now create the resource
  • Change the name fldemo to something else
az deployment group create --template-file ./mlops/bicep/open_sandbox_setup.bicep --resource-group fltest --parameters demoBaseName="fldemo22"
  • wait until the deployment is complete
  • now run the python code to setup the environment
python -m pip install -r ./examples/pipelines/fl_cross_silo_literal/requirements.txt
  • now update the config.json
"subscription_id": "<subscription-id>",
"resource_group": "<resource-group>",
"workspace_name": "<workspace-name>"
  • now run the training code
python ./examples/pipelines/fl_cross_silo_literal/ --example MNIST --submit
  • wait for the training to complete
  • Metric view
  • Steps review



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