Lecture 02 - Is Learning Feasible?
Is Learning Feasible? - Can we generalize from a limited sample to the entire space? Relationship between in-sample and out-of-sample. Lecture 2 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunes.apple.com/us/course/machine-learning/id515364596 and on the course website - http://work.caltech.edu/telecourse.html
Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND). To learn more about this license, http://creativecommons.org/licenses/by-nc-nd/3.0/
This lecture was recorded on April 5, 2012, in Hameetman Auditorium at Caltech, Pasadena, CA, USA.
Видео Lecture 02 - Is Learning Feasible? канала caltech
Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND). To learn more about this license, http://creativecommons.org/licenses/by-nc-nd/3.0/
This lecture was recorded on April 5, 2012, in Hameetman Auditorium at Caltech, Pasadena, CA, USA.
Видео Lecture 02 - Is Learning Feasible? канала caltech
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