Buy AND Build for Production Machine Learning with Nir Bar-Lev - #488

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By TWIML and Sam Charrington. Discovered by Player FM and our community — copyright is owned by the publisher, not Player FM, and audio is streamed directly from their servers. Hit the Subscribe button to track updates in Player FM, or paste the feed URL into other podcast apps.

Today we’re joined by Nir Bar-Lev, co-founder and CEO of ClearML.

In our conversation with Nir, we explore how his view of the wide vs deep machine learning platforms paradox has changed and evolved over time, how companies should think about building vs buying and integration, and his thoughts on why experiment management has become an automatic buy, be it open source or otherwise.

We also discuss the disadvantages of using a cloud vendor as opposed to a software-based approach, the balance between mlops and data science when addressing issues of overfitting, and how ClearML is applying techniques like federated machine learning and transfer learning to their solutions.

The complete show notes for this episode can be found at https://twimlai.com/go/488.

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