AI and machine learning are top priorities for nearly every company. Despite this, “productionalizing” machine learning processes is an underappreciated problem, and as a result, businesses often find themselves failing to maximize ROI from their data initiatives. Will Nowak identifies best practices and common pitfalls in bringing machine learning and AI models to production and details what the steps look like to get there.
Will Nowak is a data scientist a Dataiku, where he helps Fortune 500 companies improve data science operations. Previously, he engineered machine learning models for several Y Combinator startups, learning the pitfalls and challenges to productionalizing machine learning. Will holds a bachelor’s in math and economics from Northwestern University and a master’s in organizational leadership from Columbia University. In addition to the aforementioned topics, Will enjoys biking, coffee, and donuts and dislikes buzzwords, pretension, and meanness.
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