In this episode of MLOps Live, Sabine and Stephen are joined by Duarte Carmo, Machine Learning Engineer at Amplemarket. Duarte draws on his extensive expertise in the field to offer advice on how to effectively execute MLOps within the constraints of limited manpower and resources of a team at a reasonable scale. He describes in-depth most of the critical problems that early-stage start-ups and small teams would encounter while deploying models and how to solve them.
Unlike large corporations whose methods have popularized the field, most ML teams are small and face distinct challenges. Most companies in the machine learning sector are now functioning at a reasonable scale, which this Q&A session caters to.
In this episode of MLOps Live, Sabine and Stephen are joined by Duarte Carmo, Machine Learning Engineer at Amplemarket. Duarte draws on his extensive expertise in the field to offer advice on how to effectively execute MLOps within the constraints of limited manpower and resources of a team at a reasonable scale. He describes in-depth most of the critical problems that early-stage start-ups and small teams would encounter while deploying models and how to solve them.
Unlike large corporations whose methods have popularized the field, most ML teams are small and face distinct challenges. Most companies in the machine learning sector are now functioning at a reasonable scale, which this Q&A session caters to.
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Previous guests include: Andy McMahon of NatWest Group, Jacopo Tagliabue of Coveo, Adam Sroka of Origami, Amber Roberts of Arize AI, Michal Tadeusiak of
deepsense.ai, Danny Leybzon of WhyLabs, Kyle Morris of Banana ML, Federico Bianchi of Università Bocconi, Mateusz Opala of Brainly, Kuba Cieslik of
tuul.ai, Adam Becker of
Telepath.io and Fernando Rejon & Jakub Zavrel of Zeta Alpha Vector. Check out our three most downloaded episodes:
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