01:24:45

UCSC STAT 132 - week 3 - lecture 6 - F distribution, Method of Transformation, Multivariate Normal

54:13

UCSC STAT 132 - week 3 - lecture 5 - Chi squared and t distribution, Method of Transformation

01:25:32

UCSC STAT 132 - week 2 - lecture 4 - Change of Variables, Method of Transformation, Jacobian Matrix

50:21

UCSC STAT 132 - week 2 - lecture 3 - Normal distribution and Moment Generating Function

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UCSC STAT 132 - week 1 - lecture 2 - Gamma distribution and property of moment generating function

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UCSC STAT 132 - week 1 - lecture 1 - Moment Generating Function, Exponential, Binomial

53:16

UCSC STAT 132 - week 0 - lecture 0 - Moments, Expectation, Variance of Random Variables

25:33

Change Point Detection in Dynamic Graphs with Generative Model

49:45

UCLA Stats 100B Discussion - Week 10

50:28

UCLA Stats 403 Discussion - Week 10

47:40

UCLA Stats 403 Discussion - Week 9

49:46

UCLA Stats 100B Discussion - Week 9

49:22

UCLA Stats 100B Discussion - Week 8

49:25

UCLA Stats 403 Discussion - Week 8

50:23

UCLA Stats 100B Discussion - Week 7

48:48

UCLA Stats 100B Discussion - Week 6

46:02

UCLA Stats 403 Discussion - Week 6

46:12

UCLA Stats 100B Discussion - Week 5

50:11

UCLA Stats 403 Discussion - Week 5

46:08

Basics of Linear Regression 2

48:29

Basics of Linear Regression 1

53:22

UCLA Stats 403 Discussion - Week 3

37:17

UCLA Stats 100B Discussion 9

45:00

UCLA Stats 100B Discussion 8

36:26

UCLA Stats 100 B Discussion 7

47:43

UCLA Stats 100 B Discussion 6

39:13

UCLA Stats 100B Discussion 5

45:20

UCLA Stats 100B Discussion 3

49:35

UCLA Stats 100B Discussion 2

30:29

UCLA Stats 100B Discussion 1

35:13

Binary Search Tree: Search and Delete Node (R6 Reference Class)

23:29

Binary Search Tree in R with R6 Reference Class

30:12

UCLA Stats100B Mathematical Statistics: Bootstrap

17:30

UCLA Stats100B Mathematical Statistics: Normal, Chi-squares, T, F distribution

21:47

UCLA Stats100B Mathematical Statistics: sum of random variable & moment generating functions

30:51

Monte Carlo Integration and Importance Sampling

27:33

From Uniform to Normal Distribution - Jacobian, Box-Muller Transformation, Cholesky Decomposition

18:26

Properties of Determinant, Adjugate Matrix, Laplace Expansion, Cramer's Rule

28:09

Construct Orthonormal Basis, QR Factorization, Reflection and Projection, 4 Fundamental Subspaces

31:46

Basic Concept in Linear Algebra, Gaussian Elimination, Solving Ax=b, LU Factorization

25:23

Explaining the Arithmetics of Convolutional and Max Pooling Layer in CNN

17:03

Use Convolutional Neural Network to Recognize My Handwriting (keras in R)

16:59

Python 2: Use Convolutional Neural Network (CNN) to Recognize My Handwriting

09:17

Tableau Tutorial 82: Monte Carlo Integration

08:15

Tableau Tutorial 81: Randomly Sample Data in Tableau

03:28

Tableau Tutorial 80: Parametric Equation and Curve

11:24

Tableau Tutorial 79: Z-Test (Vizient AMC Calculator)

02:39

Tableau Tutorial 78: Customized Origin for Waterfall Chart

10:23

Python 1: Closed-Form Solution, Gradient Descent and Coordinate Descent: Multiple Regression

13:45

Scraping PDF Files in R: Vizient Quality and Accountability Scorecard

04:57

Tableau Tutorial 77: Apply Jitter in Box Plot

04:49

Tableau Tutorial 76: Sparkline (min/max highlighted) and Measure Text in Separated Column

17:55

Use Neural Network to Recognize My Handwriting after Tuning the Parameters

16:28

Leapfrog Hospital Safety Grade - Web Scraping

04:58

Tableau Tutorial 75: Break Down Aggregation by N Selections from Action/LOD/Parameter

27:06

Hospital Value Based Purchasing (VBP) Program Calculator for Payment Prediction in Tableau

14:42

R Tutorial 41: Gradient Descent for Negative Log Likelihood in Logistics Regression

22:43

R Tutorial 40: Closed-Form Solution, Gradient Descent and Coordinate Descent (Multiple Regression)

11:35

Tableau Tutorial 74: Gauge Chart (No Background Image)

08:52

Mathematics: Directional Derivative and Gradient (Tangent Plane)