05:40

MACHINE LEARNING ALGORITHMS

05:55

ARTIFICIAL INTELLIGENCE VS MACHINE LEARNING

05:30

CONCEPTS OF MACHINE LEARNING

06:38

LOGISTIC REGRESSION & MACHINE LEARNING IN R

03:29

STATISTICS IN R: LOGISTIC REGRESSION

04:40

STATISTICS IN R: LINEAR REGRESSION

04:15

STATISTICS IN R: CORRELATION

03:32

STATISTICS IN R: CHI-SQUARE TEST

06:35

STATISTICS IN R: ANOVA

05:28

STATISTICS IN R: T-TEST

05:54

STATISTICS IN R: Statistical Estimates

05:00

STATISTICS: CORRELATION, REGRESSION, ODDS RATIO

05:23

STATISTICS: CHI-SQUARE TEST

05:09

STATISTICS: ANOVA

04:35

STATISTICS: STATISTICAL ASSUMPTIONS

05:54

STATISTICS: STUDENT'S T-TEST CALCULATION

05:12

STATISTICS: STUDENT'S T-TEST

05:25

STATISTICS: CONFIDENCE INTERVAL & CONFIDENCE LEVEL

05:39

STATISTICS: p-VALUE AND SIGNIFICANCE LEVEL

04:42

STATISTICS: HYPOTHESIS

05:48

STATISTICS: STANDARD NORMAL DISTRIBUTION PART II

06:31

STATISTICS: STANDARD NORMAL DISTRIBUTION

05:11

STATISTICS: NORMAL PROBABILITY DISTRIBUTION

06:33

STATISTICS: PROBABILITY DISTRIBUTION

04:25

STATISTICS: VARIATION IN DATA

04:51

STATISTICS: WHY CUMULATIVE FREQUENCY?

06:41

STATISTICS: WHY STANDARD DEVIATION NOT VARIANCE?

05:07

STATISTICS: INTERQUARTILE RANGE

07:32

STATISTICS: MEAN, MEDIAN, MODE. WHEN TO USE THEM?

02:53

STATISTICS: WHY WE NEED IT???

09:40

PRACTICE IN R: Part 8

10:18

PRACTICE IN R: Part 7

09:34

PRACTICE IN R: Part 6

09:43

PRACTICE IN R: Part 5

07:06

PRACTICE IN R: Part 4

12:59

PRACTICE IN R: Part 3

03:11

PRACTICE IN R: Part 2

07:49

PRACTICE IN R: Part 1

05:09

Basics for R (Part 5)- Common Errors in R

04:29

Basics for R (Part 4)- While & For Loop

03:26

Basics for R (Part 3)- IF Statement

07:49

Basics for R (Part 2)- Variables & Functions

10:34

Basics for R (Part 1)- Datatypes & Data Structures