All data science projects are composed of the algorithm (model) and the data. While data scientists are natively focused on math and models, experience is showing them that for a data science project to succeed in real life, much more than a deep understanding of math is needed.
Gilad and Noa will take us through the journey their team went on in transforming from working with a model-centric to a data-centric approach.

In this episode of the Wix Engineering Podcast: how a data science team upgraded their AI by refocusing, changing their priorities, and creating a new workflow focusing on data.

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