Tom Drabas - Increase productivity and simplify data operations in Python | PyData Seattle 2023

Designing ML pipelines is a complex process involving numerous changes along the way, from a prototype to deployment. It frequently involves iterating over multiple models on a smaller scale and then converting those models to run at scale. In this talk we will discuss the inefficiencies of this process and present a modern open source based solution that helps to mitigate many of these inefficiencies. The proposed tools and approaches help data scientists, data engineers, and machine learning engineers work more efficiently across all ranges of tasks and reduce the time-to-solution. We also present future development plans.

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