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CLASSIFYING HEARTBEATS USING MACHINE LEARNING team

Capstone Program: MEngDA

MEngDA

CalCardiac: Classifying Heartbeats Using Machine Learning

December 27, 2018 by

CLASSIFYING HEARTBEATS USING MACHINE LEARNING teamCalCardiac worked to reduce false hospital alarms due to arrhythmias. Collaborating with the UCSF School of Nursing, the team used various machine learning techniques to create a browser-based utility to view and label ECG waveform images. Capstone Team: Alex Ackroyd, Adam Andrews, Siddhant Issar, Segev Malool, Umesh Thillaivasan, Yuntao Wang. Research in collaboration with Jacob… Read More »

American Jobs Project

April 24, 2017 by

Students working at a tableThe goal of this project is to help policy makers, private investors, and the general public better understand the social benefits of microgrids, through the design and implementation of a tool that uses a research-based data driven model to predict the economic impact of the development of the microgrid industry.

DODURA: Internet Deployment Optimization in Dense Urban Areas – Facebook

April 24, 2017 by

A model of city skyscrapersDODURA which stands for Deployment Optimization of Internet In Dense Urban Areas uses traffic modeling and data science to model and understand consumer demand for high bandwidth internet data in densely populated underserved urban areas. The project addresses the question of which locations in a city would be optimal candidates to deploy better internet infrastructure.

Forecasting Volume of Home Equity Lending Applications

April 24, 2017 by

Forecasting Volume of Home Equity Lending Applications capstone teamNomis Solutions is a financial services company which provides optimized home equity interest rates to commercial banks. A key input to the price optimization models they use is the expected volume of new loan applications. Our Capstone project objective is to develop a model to predict the volume of loan applications to feed their current… Read More »

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