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Some benchmarks for using Ray's implementation of joblib backend to distribute scikit-learn training.

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sklearn-ray

Some benchmarks for using Ray's implementation of joblib backend to distribute scikit-learn training.

How to run:

  1. run ray up -y blog<#nodes>.yaml.
  2. run ray attach blog<#nodes>.yaml
  3. copy the relevant <benchmark>.py to the remote cluster.
  4. run RAY_ADDRESS=auto python <benchmark>.py

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Some benchmarks for using Ray's implementation of joblib backend to distribute scikit-learn training.

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