Deploying Machine Learning Pipelines in Production: Overcoming common pitfalls

Hosted By
Matthieu Di M. and 2 others

Details
Building a machine learning model that can predict well is one challenge, productionizing it is quite another challenge. How to ensure stability and speed over time and as your data grows in size? How to measure and prevent drift? Come hear about the experiences of machine learning engineers at Google, Stripe, and Shopify.
### Speakers ###
- Julia Evans, Software Engineer, Stripe
- Philippe Hamel, Machine Learning Engineer, Google
- Peng Yu, Merchant Optimization Developer, Shopify
### Schedule ###
6:00 | Doors open
6:30 | Presentations
Co-hosted by Breather, Shopify, and MTL DATA

MTL Data
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Breather HQ
5605 Ave de Gaspé, suite 701 · Montréal, QC
Deploying Machine Learning Pipelines in Production: Overcoming common pitfalls