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01:23:23 Lecture 10/21/21: Ensembles + Regularization Lecture 10/21/21: Ensembles + Regularization	Lecture 10/21/21: Ensembles + Regularization Zoom Recording ID: 94347618999 UUID: Hg/UOyaZTFGi+ub+trRDtw== Meeting Time: 2021-10-21T13:31:18Z tree trees prediction model variance models loss thing gradient bootstrap samples predictions dataset regularization error learners idea function training values From Madeleine Udell 79 plays
01:26:58 Lecture 10/14: Bootstrap and bias variance… Lecture 10/14: Bootstrap and bias variance tradeoff	Lecture 10/14: Bootstrap and bias variance tradeoff Zoom Recording ID: 94347618999 UUID: qgdVNfgoTIi+Z1Xj3EkLqQ== Meeting Time: 2021-10-14T13:29:44Z model dataset function distribution variance points prediction bootstrap point sample models datasets expectation sigma thing linear hm times bias epsilon From Madeleine Udell 127 plays
01:20:10 ORIE 4580 - Lecture 13 - 1015 ORIE 4580 - Lecture 13 - 1015	ORIE 4580 - Lecture 13 - 1015 distribution thing test likelihood statistic chi points probability bootstrap parameters sense lambda function bins hypothesis problem point things end question From Sid Banerjee 48 plays Content Categories Lectures Creation Date October 15, 2020 Creator 1 First Name Sid Creator 1 Last Name Banerjee Creator 1 Role Lecturer Creator 1 NetID sb2373
01:19:00 ORIE 4580 - Lecture 11 - 1008 ORIE 4580 - Lecture 11 - 1008	ORIE 4580 - Lecture 11 - 1008 process poisson lambda probability distribution thing rate minus property arrivals processes arrival definition problem sense times point lot model bootstrap From Sid Banerjee 80 plays Content Categories Lectures Creation Date October 08, 2020 Creator 1 First Name Siddhartha Creator 1 Last Name Banerjee Creator 1 Role Lecturer Creator 1 NetID sb2373