Machine Learning, a subfield of computer science, involves the development of mathematical algorithms that discover knowledge from specific data sets, and then "learn" from the data in an iterative fashion that allows predictions to be made. Today, Machine Learning has a wide range of applications, including natural language processing, search engine functionality, medical diagnosis, credit card fraud detection, and stock market analysis.
This symposium — the tenth in an ongoing series presented by the Machine Learning Discussion Group at the New York Academy of Sciences — will feature Keynote Presentations from leading scientists in both applied and theoretical Machine Learning.
|Member (Student / Postdoc / Resident / Fellow)
|Nonmember (Student / Postdoc / Resident / Fellow)
Three of the keynote addresses for this meeting will be presented via Livestream. For full details, and to view the Livestreams, use the link below: