Project Name: Data at the Museum
The NY Metropolitan Museum classifies roughly 2400 of their 480,000 items as ‘Highlights’. Our team used supervised and unsupervised learning techniques to determine what factors contribute to an item being a highlight, and created a model to predict whether an item in the collection should be identified as such. This model could be used by the Met to determine what pieces to feature in upcoming exhibitions, or by other museums to identify what under-appreciated items to request on loan for their galleries.
The value I provide is greater than the cost of doing otherwise.
understanding where the underlying value can be found, and to be able to create a model that reveals it to everyone else.
Rochester, New York
Inquisitive, Collaborative, and Communicative
Technical, Team-based, Specialist