Reproducibility in machine learning
This webinar presents a brief introduction to “repeatable research” in machine learning. To make good use of research results, students and researchers must learn to gradually adopt new working methods in order to gain in productivity.
Activity offered in French only
This webinar presents a brief introduction to “repeatable research” in machine learning.
To make good use of research results, students and researchers must learn to gradually adopt new working methods in order to gain in productivity.
No prior knowledge is required.
This webinar is presented by IID (Institute Intelligence and Data) of Université Laval
Speaker
Ph.D. student in Computer Science, Université Laval
David Beauchemin is a Ph.D. student in Computer Science at Université Laval with expertise in actuarial science, computer science and software engineering. He specializes in automatic processing of natural language using machine learning. He has had a foothold in industry throughout his academic career by applying his theoretical knowledge to real problems which businesses are facing.
Together with his colleagues, he recently founded Baseline, a cooperative of AI experts wishing to contribute to the transfer of technology between academia and business.
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