Yaser Abu-Mostafa

 

 


 

Yaser S. Abu-Mostafa is a Professor of Electrical Engineering and Computer Science at the California Institute of Technology. His main fields of expertise are machine learning and computational finance.

Dr. Abu-Mostafa received the Clauser Prize for the most original doctoral thesis at Caltech. He received the ASCIT Teaching Awards in 1986, 1989 and 1991, the GSC Teaching Awards in 1995 and 2002, and the Richard P. Feynman prize for excellence in teaching in 1996. He was the founding Program Chairman of the annual conference on Neural Information Processing Systems (NIPS), and a founding member of the IEEE Neural Networks Council. He chaired the second and fourth international conferences on Neural Networks in the Capital Markets (NNCM-94 and NNCM-96), and the sixth international conference on Computational Finance (CF-99). He received the Kuwait State Award in Applied Science in 1999. In 2005, the Hertz Foundation established a perpetual graduate fellowship named the Abu-Mostafa Fellowship in his honor.

Dr. Abu-Mostafa currently serves on a number of scientific advisory boards, and has served as a technical consultant on machine learning for several companies, including Citibank for 9 years. He has numerous technical publications including 3 articles in Scientific American, as well as several keynote lectures at international conferences.

More info: http://work.caltech.edu/




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Sep 18th 2016

Introductory Machine Learning course covering theory, algorithms and applications. Our focus is on real understanding, not just "knowing."

Average: 6 (2 votes)
Sep 25th 2014

Introductory Machine Learning course covering theory, algorithms and applications. Our focus is on real understanding, not just "knowing."

Average: 10 (1 vote)
Self Paced

A real Caltech course, not a watered-down version. This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications.

Average: 6.2 (27 votes)