Why are we training ML models wrong and how can feature stores help? - Episode 101

04/05/2021 19 min
Why are we training ML models wrong and how can feature stores help? - Episode 101

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Episode Synopsis

In this week's episode, we talk about the problem of data leakage, which occurs when data scientists feed data that did not exist during the time of a past event to machine learning models. Monte Zweben, CEO of Splice Machine talks about how feature stores can help with this issue by validating when a data set actually occurred and then correcting these point-in-time consistency issues.

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