Machine Learning Operations: Applying DevOps to Data Science

Microsoft Ignite 2019 | Machine Learning Operations: Applying DevOps to Data Science | Damian Brady
Course info
Level
Advanced
Updated
Feb 12, 2020
Duration
45m
Table of contents
Machine Learning Operations: Applying DevOps to Data Science
Description
Course info
Level
Advanced
Updated
Feb 12, 2020
Duration
45m
Description

Many companies have adopted DevOps practices to improve their software delivery, but these same techniques are rarely applied to machine learning projects. Collaboration between developers and data scientists can be limited and deploying models to production in a consistent, trustworthy way is often a pipe dream. In this session, learn how Tailwind Traders applied DevOps practices to their machine learning projects using Azure DevOps and Azure Machine Learning Service. We show automated training, scoring, and storage of versioned models, wrap the models in Docker containers, and deploy them to Azure Container Instances or Azure Kubernetes Service. We even collect continuous feedback on model behavior so we know when to retrain.

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About the author

Microsoft Ignite is the place to learn from the experts, connect with your community, and explore the digital session catalog of the latest technology.

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