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Data Mining
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Data Mining | Trouble- Free
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Course Details
Course Lessons
28
Course Period
3h 51m
No.Students
1
Language
English
Prerequisite
Data Warehouse (DWH)
(
1)
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Course Lessons
1 |
#1 Introduction To Data Mining, Types Of Data DM
00:10:41
2 |
#2 Data Mining Functionalities DM
00:16:14
3 |
#3 Interestingness Of Patterns - What are Interesting Patterns DM
00:07:35
4 |
#4 Classification Of Data Mining Systems DM
00:05:16
5 |
#5 Data Mining Task Primitives DM
00:08:59
6 |
#6 Integration Of Data Mining System with A Database or Data Warehouse DM
00:06:53
7 |
#7 Major Issues In Data Mining DM
00:07:38
8 |
#8 Data Preprocessing In Data Mining - 4 Steps DM
00:18:01
9 |
#9 Frequent Patterns - Example, Market Basket Analysis DM
00:10:14
10 |
#10 Mining Methods - APRIORI algorithm with Example DM
00:11:21
11 |
#11 Mining Methods - FP Growth algorithm with Example DM
00:11:14
12 |
#12 Mining Various Kinds Of Association Rules DM
00:08:25
13 |
#13 Correlation Analysis - Pearson's Correlation Coefficient DM
00:08:34
14 |
#14 Constraint Based Association Mining DM
00:07:14
15 |
#15 Graph Pattern Mining in Data Mining DM
00:05:05
16 |
#16 Sequential Pattern Mining ( SPM ) DM
00:07:42
17 |
#17 Classification & Prediction - Example, Steps DM
00:08:06
18 |
#18 Decision Tree Induction - with Example DM
00:06:44
19 |
#19 Bayesian Classification - Bayes Theorem, Naive Bayes Classifier DM
00:02:57
20 |
#20 Rule Based Classifier with Example DM
00:04:26
21 |
#21 Lazy Learners In Data Mining - KNN Algorithm DM
00:03:37
22 |
#22 Cluster Analysis - Properties, Categories Of Methods DM
00:04:45
23 |
#23 Types Of Data In Cluster Analysis DM
00:10:22
24 |
#24 Partitioning Clustering - K Means Algorithm DM
00:10:04
25 |
#25 Hierarchical Clustering - Agglomerative & Divisive Algorithm DM
00:07:31
26 |
#26 Density Based Clustering - DBSCAN Algorithm DM
00:07:14
27 |
#27 Grid Based Clustering - STING Algorithm DM
00:07:20
28 |
28 Outlier Analysis, Types, Outlier Detection & Techniques DM
00:07:16
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