42:02

452 S21 Lecture 22 - Karlin-Rubin

01:13:20

452 S21 Lecture 21 - Most Powerful Tests

01:01:23

688 S21 Lecture 22 - Nonparametric Regression

17:53

688 S21 Lab 23 - Kernel PCA

01:11:09

452 S21 Lecture 20 - Likelihood Ratio Test

01:02:22

688 S21 Lecture 23 - Kernel PCA

23:08

688 S21 Lab 22 - Nonparametric Regression

01:11:46

452 S21 Lecture 19 - Hypothesis Testing

01:02:15

688 S21 Lecture 20 - Bagging and RFs

21:18

688 Lab 20 - Bagging and RFs

21:36

688 S21 Lab 21 - Boosting

01:10:48

452 S21 Lecture 18 - MLE Asymptotics

01:04:28

688 S21 Lecture 21 - Boosting

01:10:25

452 S21 Lecture 17 - Central Limit Theorem

13:17

688 S21 Lab 18 - More Clustering

59:07

688 S21 Lecture 18 - More Clustering

58:52

688 Lecture 19 - Trees

19:45

688 Lab 19 - Trees

01:06:18

688 Lecture 17 - Clustering

13:33

688 Lab 17 - Clustering

01:12:09

688 S21 Lecture 15 - PCA

01:09:55

688 S21 Lecture 16 - PCR

20:15

688 S21 Lab 15 - PCA

16:55

688 S21 Lab 16 - PCR

01:10:25

452 S21 Lecture 15 - More Convergence

01:12:47

452 S21 Lecture 16 - LLNs and CLTs

55:50

688 S21 Lecture 14 - LASSO

15:36

688 S21 Lab 14 - LASSO

01:11:22

452 S21 Lecture13 - Lehmann-Scheffe

01:11:28

452 S 21 Lecture 14 - Inequalities and Convergence

01:17:09

452 S21 Lecture 11 - Attainment

01:08:19

452 S21 Lecture 12 - Rao-Blackwell

01:04:44

688 S21 Lecture 13 - Ridge Regression

20:48

688 S21 Lab 13 - Ridge Regression

01:17:09

452 S21 Lecture 11 - CRLB Attainment

01:10:28

452 S21 Lecture 10 - Cramer-Rao Lower Bound

13:52

688 Lab 12 - Variable Selection

01:01:09

688 S21 Lecture 11 - Logistic Regression

01:11:42

688 S21 Lecture 12 - Variable Selection

24:09

688 S21 Lab 11 - Logistic Regression

24:02

688 S21 Lab 10 -- More LDA and QDA

58:53

688 S21 Lecture 10 - LDA and QDA

01:07:31

688 Lecture 9 - Linear Classifiers

01:19:26

452 S21 Lecture 8 - UMVUEs

01:16:08

452 S21 Lecture 9 - Fisher Information

31:09

688 S21 Lab 8 - More KNN

17:37

688 S21 Lab 9 - LDA

50:06

688 S21 Lecture 8 - Classification

01:09:21

688 S21 Lecture 7 - Minimum Risk Regression and Classification

11:29

688 S21 Lab 7 - KNN Classification

01:08:54

688 S21 Lecture 6 - Bias-Variance Tradeoff

01:21:10

452 S21 Lecture 7 - Evaluation

01:20:20

452 S21 Lecture 6 - More MLEs

13:00

688 S21 Lab 6 - Evaluation

51:48

688 S21 Lecture 5 - Evaluation

30:33

688 S21 Lab 4 - KNN

01:17:34

452 S21 Lecture 4 - Method of Moments

01:16:33

452 S21 Lecture 5 - Maximum Likelihood Estimation

31:56

688 S21 Lab 5 - Evaluation

51:50

688 S21 Lecture 4 - KNN