Beat the Crowds @ UMass

An attempt for time-series data prediction at HackUMass 2019

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Project Date HackUmass 2019
Role Worked on the model

Our team won the Wolfram sponsor award by Wolfram Research. Developed a mobile app that leverages machine-learning to predict dining common busy-ness and identify student dining habits, for use by students and UMass Dining.

Our project consists of a React Native application that interacts with a Prophet forecasting procedure deployed on a Flask server hosted by Digital Ocean. I worked on deploying a model using the open-source time series prediction mechanism called Facebook Prophet to make a sensitive model in python for accurate predictions.