DATA MINING (DM)
5.0
(2)
32 learners
What you'll learn
This course includes
- 3.5 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 28 lessons • 3.5 hours of video
DATA MINING (DM)
28 lessons
• 3.5 hours
DATA MINING (DM)
28 lessons
• 3.5 hours
- #1 Introduction To Data Mining, Types Of Data |DM| #dm #data #datamining #jntu #btech 10:41
- #2 Data Mining Functionalities |DM| 16:14
- #3 Interestingness Of Patterns - What are Interesting Patterns |DM| 07:35
- #4 Classification Of Data Mining Systems |DM| 05:16
- #5 Data Mining Task Primitives |DM| 08:59
- #6 Integration Of Data Mining System with A Database or Data Warehouse |DM| 06:53
- #7 Major Issues In Data Mining |DM| 07:38
- #8 Data Preprocessing In Data Mining - 4 Steps |DM| 18:01
- #9 Frequent Patterns - Example, Market Basket Analysis |DM| 10:14
- #10 Mining Methods - APRIORI algorithm with Example |DM| 11:21
- #11 Mining Methods - FP Growth algorithm with Example |DM| 11:14
- #12 Mining Various Kinds Of Association Rules |DM| 08:25
- #13 Correlation Analysis - Pearson's Correlation Coefficient |DM| 08:34
- #14 Constraint Based Association Mining |DM| 07:14
- #15 Graph Pattern Mining in Data Mining |DM| 05:05
- #16 Sequential Pattern Mining ( SPM ) |DM| 07:42
- #17 Classification & Prediction - Example, Steps |DM| 08:06
- #18 Decision Tree Induction - with Example |DM| 06:44
- #19 Bayesian Classification - Bayes Theorem, Naive Bayes Classifier |DM| 02:57
- #20 Rule Based Classifier with Example |DM| 04:26
- #21 Lazy Learners In Data Mining - KNN Algorithm |DM| 03:37
- #22 Cluster Analysis - Properties, Categories Of Methods |DM| 04:45
- #23 Types Of Data In Cluster Analysis |DM| 10:22
- #24 Partitioning Clustering - K Means Algorithm |DM| 10:04
- #25 Hierarchical Clustering - Agglomerative & Divisive Algorithm |DM| 07:31
- #26 Density Based Clustering - DBSCAN Algorithm |DM| 07:14
- #27 Grid Based Clustering - STING Algorithm |DM| 07:20
- 28 Outlier Analysis, Types, Outlier Detection & Techniques |DM| 07:16
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