Data Mining Course Instructor
Course Details
- No Of Lessons 36
- Duration 15h 56m
- Language English
- No Of Students 18
- Prerequisite Data Warehouse (DWH)
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Data Mining Course Lessons
- 1 | Lecture 1 Introduction, Knowledge Discovery Process 00:23:12
- 2 | Lecture 2 Data Preprocessing - I 00:36:13
- 3 | Lecture 3 Data Preprocessing - II 00:26:19
- 4 | Lecture 4 Association Rules 00:27:27
- 5 | Lecture 5 Apriori algorithm 00:27:01
- 6 | Lecture 6 : Rule generation 00:22:57
- 7 | Lecture 7 : Classification 00:10:56
- 8 | Lecture 8 : Decision Tree - I 00:31:57
- 9 | Lecture 9 : Decision Tree - II 00:27:16
- 10 | Lecture 10 : Decision Tree III 00:29:21
- 11 | Lecture 11 : Decision Tree IV 00:11:06
- 12 | Lecture 12 : Bayes Classifier I 00:29:13
- 13 | Lecture 13 : Bayes Classifier II 00:30:46
- 14 | Lecture 14 : Bayes Classifier III 00:29:25
- 15 | Lecture 15 : Bayes Classifier IV 00:25:12
- 16 | Lecture 16 : Bayes Classifier V 00:26:09
- 17 | Lecture 17 : K Nearest Neighbor I 00:29:38
- 18 | Lecture 18 : K Nearest Neighbor II 00:24:44
- 19 | Lecture 19 : 00:29:49
- 20 | Lecture 20 00:26:55
- 21 | Lecture 21 00:24:27
- 22 | Lecture 22 : Support Vector Machine I 00:24:35
- 23 | Lecture 23 : Support Vector Machine II 00:23:20
- 24 | Lecture 24 : Support Vector Machine III 00:27:39
- 25 | Lecture 25 : Support Vector Machine IV 00:30:09
- 26 | Lecture 26 : Support Vector Machine V 00:28:11
- 27 | Lecture 27: Kernel Machines 00:28:52
- 28 | Lecture 28: Artificial Neural Networks I 00:27:06
- 29 | Lecture 29:Artificial Neural Networks II 00:25:57
- 30 | Lecture 30: Artificial Neural Networks III 00:28:40
- 31 | Lecture 31: Artificial Neural Networks IV 00:28:28
- 32 | Lecture 32: Clustering I 00:26:58
- 33 | Lecture 33: Clustering II 00:27:20
- 34 | Lecture 34: Clustering III 00:27:25
- 35 | Lecture 35: Clustering IV 00:26:25
- 36 | Lecture 36: Clustering V 00:25:03
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