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 - and on the course website -

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,

This lecture was recorded on April 5, 2012, in Hameetman Auditorium at Caltech, Pasadena, CA, USA.

Machine Learning (Field Of Study),Caltech,MOOC,data,computer,science,course,Data Mining (Technology Class),Big Data,Data Science,learning from data,in sample,out of sample,bin model,Hoeffding,Technology (Professional Field),Computer Science (Industry),Learning (Quotation Subject),Lecture (Type Of Public Presentation),California Institute Of Technology (Organization),Theory (Quotation Subject),Abu-Mostafa,Yaser,