Room: Room 203
April 5
14:00–14:25
Machine learning models are a new artifact to build, version and deploy, explore there impacts on your architecture.
Having dealt at least once with deploying a machine learning model in production.
CI/CD is a well-known tool for craftsmen, enabling them to build and deploy their applications automatically and robustly. ML brings an additional artifact to building the Machine Learning model. Extracted from the book Culture MLOps, in this talk we'll explore the impact of ML model management on CI/CD. Based on 3 needs (making a prototype, starting to develop a product, scaling up), we'll see where to build the model, in which register to version it, and how to deploy a new version.
You'll leave with different patterns that can be applied in your own context.
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Emmanuel-Lin Toulemonde is looking for two things: learning and sharing.
He has been working in Data Science since 2014 and in software development since 2017. He is currently MLOps manager at OCTO Technology and trainer at OCTO Academy.
He carries out and helps to carry out projects involving data or Machine Learning. Looking for better ways of doing things, he learns from other disciplines. He strives to give back to the community what he has learned in the form of an article, a book and here a conference.
His subjects of interest are: data science, MLEng, MLOps, monitoring data science systems, interpretability of data science systems, software development, emergent architecture, agility, etc.