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Michael Irwin Jordan ForMemRS [6] (born February 25, 1956) is an American scientist, professor at the University of California, Berkeley, research scientist at the Inria Paris, and researcher in machine learning, statistics, and artificial intelligence.
She served as an advisor for Deep Learning Indaba, a non-profit which looks to train African people in machine learning. In 2017 she was selected by Forbes magazine as one of 20+ "leading women" in artificial intelligence. [18] Thomas has also written on the application of data science and machine learning in medicine.
Pedro Domingos, The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World, New York, Basic Books, 2015, ISBN 978-0-465-06570-7. Pedro Domingos, "Our Digital Doubles: AI will serve our species, not control it", Scientific American, vol. 319, no. 3 (September 2018), pp. 88–93.
This is a list of universities in the United States classified as research universities in the Carnegie Classification of Institutions of Higher Education. Research institutions are a subset of doctoral degree-granting institutions and conduct research. These institutions "conferred at least 20 research/scholarship doctorates in 2019-20 and ...
There, he pursued research in artificial intelligence and machine learning as well as introducing what may have been the first on-line Black History Database. [4] After earning his PhD from the Massachusetts Institute of Technology in 1998, Isbell joined AT&T Labs – Research. In the fall of 2002, he returned to Georgia Tech to join the ...
He founded an AI company and holds a PhD in machine learning, and he was the dean of AI and Human Health at the Icahn School of Medicine at Mount Sinai in New York City.
Mila is both a research and educational institution, providing postdoc and internship positions, and providing a research environment for students enrolled in their respective universities and working towards their graduate degrees such as PhD and Master's degrees in machine learning. Mila members have also contributed to open-source software.
Littman's research interests are varied but have focused mostly on reinforcement learning and related fields, particularly, in machine learning more generally, game theory, computer networking, partially observable Markov decision process solving, computer solving of analogy problems and other areas. He is also interested in computing education ...
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