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As machine learning moves from being a research discipline to a software one, it is useful to catalog tried-and-proven methods to help engineers tackle frequently occurring problems that crop up during the ML process. In this talk, I will cover five patterns (Hashed Feature, Neutral Class, Stateless Serving Function, Bridged Schema, Feature Store) that academic researchers often don’t think about but are very useful in practical situations that arise in industry. 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