
Bringing DevOps Best Practices into Machine Learning with Benedikt Koller from ZenML
Episode · 7 Plays
Episode · 7 Plays · 1:28:19 · Mar 2, 2021
About
Benedikt Koller is a self-professed "Ops guy", having spent over 12 years working in roles such as DevOps engineer, platform engineer, and infrastructure tech lead at companies like Stylight and Talentry in addition to his own consultancy KEMB. He's recently dove head first into the world of ML, where he hopes to bring his extensive ops knowledge into the field as the co-founder of Maiot, the company behind ZenML, an open source MLOps framework.Learn more:https://zenml.io/https://maiot.io/Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: https://www.cyou.ai/newsletterFollow Charlie on Twitter: https://twitter.com/CharlieYouAISubscribe to ML Engineered: https://mlengineered.com/listenComments? Questions? Submit them here: http://bit.ly/mle-surveyTake the Giving What We Can Pledge: https://www.givingwhatwecan.org/Timestamps:02:15 Introducing Benedikt Koller05:30 What the "DevOps revolution" was10:10 Bringing good Ops practices into ML projects30:50 Pivoting from vehicle predictive analytics to open source ML tooling34:35 Design decisions made in ZenML39:20 Most common problems faced by applied ML teams49:00 The importance of separating configurations from code55:25 Resources Ben recommends for learning Ops57:30 What to monitor in an ML pipelines01:00:45 Why you should run experiments in automated pipelines01:08:20 The essential components of an MLOps stack01:10:25 Building an open source business and what's next for ZenML01:20:20 Rapid fire questionsLinks:ZenML's GitHubMaiot BlogThe Twelve Factor App12 Factors of reproducible Machine Learning in productionSeldonPachydermKubeFlowSomething Deeply HiddenThe Expanse SeriesThe Three Body ProblemExtreme Ownership
1h 28m 19s · Mar 2, 2021
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