Building Trust in Data
Trust is the cornerstone of professional growth, enabling opportunities for larger projects, promotions, and role transitions. Understanding the evaluation metrics of data science projects is crucial, as different teams prioritize various aspects, from model deployment to research publication. The stage of a company's data maturity also influences the responsibilities of data professionals, whether it's engineering existing models or developing new products from scratch.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
803: How to Thrive in Your (Data Science) Career — with Daliana Liu
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