Related projects
Discover more projects across a range of sectors and discipline — from AI to cleantech to social innovation.
Distributed collaborative recommendation engine for Asset Store
In this project we attempt to research and develop from ground up a scalable distributed computing based recommendation engine using machine learning. A computer science student from the University of Toronto will work with Side Effects Software at their Toronto office to implement the research intensive recommendation engine algorithm and integrate it in the smart asset online store. We expect and hope that this will result in high quality recommendation, is scalable and has a strong foundation in statistical machine learning based algorithm approach.
Faculty Supervisor:
Dr. Eugene Fiume
Student:
Abbas Attarwala
Partner:
Side Effects Software
Discipline:
Computer science
Sector:
Information and communications technologies
University:
University of Toronto
Program:
Accelerate
Current openings
Find the perfect opportunity to put your academic skills and knowledge into practice!
Find Projects
International
Load More
International
Load More
