Today we're talking to Philip Pilgerstorfer. We talk about his path from econometrics to data science, the importance of correlation versus causation, and how MLOps is unlocking machine learning at scale.

Philip's belief is that "machine learning is eating the world". This might sound a little scary at first, but further reinforces why we need practitioners like Philip who can unpack this complex discipline, and shine a light on both its potential impact, as well as its limitations. Philip also gives us a deep dive on a real-world machine learning use case, and leverages this example to explain core concepts like causation and model deployment at scale.

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