Machine Learning Open Source Open Science, RPI
Instructor(s): Malik Magdon-Ismail/Thilanka Munasinghe

Office: 312/315 Lally
Tel: 276-4857/276-
Office Hours: F 9:00-10:00am. /F 9:00-10:00am. (Or by appointment.)
Email: magdonatgmaildotcom/munastatrpidotedu
E-meeting place: https://rensselaer.webex.com/meet/magdon74 (as needed)

SUMMARY
A structured, intensive research experience for students interested in Machine Learning, AI and Data. Students will focus on a single research project through the semester to answer a novel research question within an open source, open science framework. Projects will use data from a variety of application domains including medical (e.g. disease modeling), environment, finance, text, image, etc. The primary outcomes for students will be open source tools and research publications in peer-reviewed venues. Prerequisites: Registration is by permission of instructor only. Students must have prior extensive knowledge in Machine Learning (for example a high passing grade in a 4xxx-level Machine Learning course) and be proficient in calculus, linear algebra, probability, algorithms and programming.

Course Information
Research Primer