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

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

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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This Week In Machine Learning & AI - 5/20/16: AI at Google I/O, Amazon's Deep Learning DSSTNE

This Week In Machine Learning & AI - May 20, 2016. Google I/O, deep learning hardware and an AI to save you from conference call hell.

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