Friday 1:10 PM–1:50 PM in Room 2
PyData in Production: Lesson Learned from Various PyData Deployment Strategies
Josh Howes
- Audience level:
- Intermediate
Description
We all love Pandas, Sklearn and the rest of the PyData stack. They allow us to conduct complex analysis and implement cutting-edge machine learning models simply and easily. However after the initial model fitting a common challenge often arises - how do we put these models in production ensuring that it fits into a larger organizational architecture? In this talk we outline the various strateg
Abstract
The PyData stack offers a remarkably powerful toolkit for building complex machine learning and analytical components quickly. However, machine learning doesn't happen in a vacuum. It is part a large system of enterprise software responsible for data processing and must play-well with other tools in the ecosystem. In order to get the benefits of rapid development while not sacrificing the non-functional requirements, MaxPoint as implemented and tested multiple deployment models for software relying on the PyData stack. This talk we walk through these various deployment models and discuss the trade-offs of the approach.
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