Are We Solving The Right Problem?
We are living in an exciting time where Machine Learning theory for common applications is maturing, open source tools are plenty, and computation is cheap. While this enables us to move faster than ever, it also makes it easy to throw latest technology at any given problem with little preparation. This can lead to overly complex solutions, suboptimal processes, and waste time. In this talk I’ll draw examples from real applications to show the necessity of spending time on defining the problem accurately before diving for solutions.
Negin Nejati received her Ph.D. in Electrical Engineering from Stanford University. Her thesis was focused on Machine Learning and Cognitive Sciences. She joined Apple Maps in 2013 where she led the geosearch effort building a query understanding Machine Learning model and geo search backend. She joined Airbnb in 2016 and is currently focused on improving customer support through Machine Learning. She enjoys building end to end products and her focus is on Natural Language Understanding.