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Data Science Workbench - clarifications


Data Science Workbench - clarifications


Hi All


I am evaluating DS WorkBench, so appreciate your views on how Data Science Workbench supports the following:


- Model Parallelism: Support of Horovod out of the box?

- Platform Agnostic: Any platform specific implementation. How easy to migrate to other platforms?

- Language Supported: Python, R

- Framework Supported: Scikit Learn, XGBoost, Tensor, Keras, MXNet, etc

- Collaborative Environment: Can share experiments, models with teams.

- Integration with MLFlow: To creating platform agnostic model formats: Edge, Tensor Serving, SparkML, Pickle, etc.

- CI/CD Pipelines support

- AB Testing

- Monitoring




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