New Contributor
Posts: 4
Registered: ‎05-11-2019

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