Show The Graduate Center Menu

Faculty

 
Sos Agaian
Graduate Center
Website

Asohan Amarasingham
City College of New YorkGraduate Center
Website

Chen Chao
Queens College
Website

Susan Epstein
Hunter College
Website

Elena Filatova
Graduate CenterNew York City College of Technology
Website

Robert M Haralick
Graduate Center
Website

Susan Imberman
College of Staten Island
Website

Raffi Khatchadourian
Graduate CenterHunter College

Devorah Kletenik
Brooklyn College

Michael Mandel
Brooklyn College
Website

Theodore Raphan
Brooklyn College
Website

Alla Rozovskaya
Queens College
Website

Ashwin Satyanarayana
Graduate CenterNew York City College of Technology
Website

Lei Xie
Hunter College
Website

Jia Xu
Graduate CenterHunter College
Website

Bo Yuan
Graduate Center
Website

Changhe Yuan
Queens College
Website

Sarah Zelikovitz
College of Staten Island
Website

Zhigang Zhu
City College of New York
Website

 
 

Machine Learning

Bayes Gain

Machine learning is a branch of artificial intelligence, concerned with the construction and study of systems that can learn from data. Learning means to make accurate predictions or useful decisions based on past observations and experience. Machine learning has matured to be a highly successful discipline with applications in many areas such as natural language processing, speech recognition, medical image analysis, document image analysis, computer vision, or predicting properties of drugs and genes. The anthropomorphic term learning of the machine learning phrase means being able to predict some unobserved components of the data given some observed components of the data. Other terms related to machine learning are pattern recognition and big data analysis. The data used in machine learning may be numeric or symbolic and typically has the form of an N-tuple, a graph, network or relation.


Courses

 

List of courses to come.