03:55

Character Recorder

21:29

Ch6 Police shooting 2

19:14

Ch6 FP-growth 2

09:52

Ch4 OLAP and Star Net

23:23

Ch 10 clustering on police shooting part 2

16:17

Ch6 Apriori Improvements

07:56

Ch 10 Intro

17:47

Ch3 Curse of Dimentionality

20:01

Ch12 High Dimensional Data

09:33

Conflict Resolver: Find Category

27:02

Ch 10 DENCLUE

05:45

Ch4 Group by

08:39

Chapter 2: Cosine similarity

12:28

Pattern evaluation

27:25

Ch 8 Attribute Selection

23:29

Ch3 Dim Reductions

06:32

Ch9 multiclass classification

13:30

Ch3 Numerosity

24:36

Ch4 Data Cube

34:47

Ch8 Classification Basics

09:03

Ch 10 on-class svm

11:27

Ch6 FP-Growth 1

13:35

Ch9 SVM the kernel trick

11:36

Conflict Resolver: Definitions and Add Term

06:34

Ch8 Information Entropy

08:39

CH9 BBN inference complete

17:21

Ch 10 CLIQUE

19:12

Ch4 Policeshooting-OLAP

28:28

Ch8 Improve Accuracy

08:45

Ch8 Tree Pruning

08:15

Ch4 cube and array

12:53

Ch4 DW architecture

16:57

Ch9 BBN Intro

07:17

Ch9 BBN probablity review

15:00

Ch3 Transformation

08:15

Ch 10 Clustering using Police Shooting Data 1

15:41

Ch9 ANN examples

16:16

Ch 12 Statistical Methods

22:57

Ch3 Chi-Merge

03:10

bug

12:07

Ch 10 number of partitions

29:47

Ch4 Data warehouse implementation

15:20

Ch3 PCA

20:25

Proximity Methods

16:27

Ch9 BBN learn a BBN

17:56

Ch10 cluster evaluation

01:30

Ch8 Conditional Entropy

02:40

Ch4 Group by 2

14:51

Ch9 ANN Intro

43:04

Ch 9 Police shooting SVM

11:21

Ch9 Transfer Learning

25:42

Ch6 police shooting 1

25:21

Ch10 Birch

04:41

Ch12 Clustering Methods

08:28

Data mining processes

15:08

What kinds of Data

13:22

Ch10 Other general intro topics

38:42

Police shooting.Know your data

15:09

Ch4 Data Warehouse Design

14:42

Ch10 basic hirachical clustering