Abstract. Machine learning (ML) components are increasingly becoming indispensable parts of software systems in every sector. Various sources agree on a compound annual growth rate of about 40% in global ML market by 2029. Yet, Gartner estimates that about 85% of ML projects fail.
Among top reasons of failures is disconnect of data science and software engineering. In this talk, I will discuss my experience in and research on building software systems with an ML component.
Dr. Jeffrey Chrabaszcz is a machine learning research scientist at Carnegie Mellon University, where his research focuses on software architecture for machine learning systems. He holds a BA in Psychology from the George Washington University and a PhD in Neuroscience and Cognitive Sciences from University of Maryland, College Park.
Previously, Dr. Chrabaszcz was the founding member of the Data Science and Machine Learning team at the data company Govini, winner of a US$400M contract with the US Department of Defense. He helped the agent-based modeling company Epistemix, which closed their series A last year. Since 2010, Dr. Chrabaszcz has run a statistical consultancy focused on medical device and pharmaceutical companies.
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