A Collaborative Data Science Development Workflow

May 26, 2021 05:00 PM (PT)

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Collaborative data science workflows have several moving parts, and many organizations struggle with developing an efficient and scalable process. Our solution consists of data scientists individually building and testing Kedro pipelines and measuring performance using MLflow tracking. Once a strong solution is created, the candidate pipeline is trained on cloud-agnostic, GPU-enabled containers. If this pipeline is production worthy, the resulting model is served to a production application through MLflow.

In this session watch:
Nicholas Hale, Data Scientist, Trillion Technology Solutions


Nicholas Hale

Nick Hale is a Senior R&D Specialist at Trillion Technology Solutions. Nick leads AI/ML initiatives at Trillion to support public sector customers. He has worked on AI/ML related Department of Defen...
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