WekaMOOC

0:10:29

Advanced Data Mining with Weka (3.4: Using R to run a classifier)

0:01:15

WEKA Introduction

0:09:00

Advanced Data Mining with Weka (2.4: MOA classifiers and streams)

0:08:15

More Data Mining with Weka (3.2: Generating decision rules)

0:12:05

Advanced Data Mining with Weka (4.4: Map tasks and Reduce tasks)

0:09:47

More Data Mining with Weka (5.4: Meta-learners for performance optimization)

0:07:26

More Data Mining with Weka (5.6: Summary)

0:06:46

Advanced Data Mining with Weka (4.1: What is distributed Weka?)

0:13:49

Advanced Data Mining with Weka (3.3: Using R to plot data)

0:07:53

More Data Mining with Weka (1.3: Comparing classifiers)

0:07:49

Data Mining with Weka (5.1: The data mining process)

0:06:30

More Data Mining with Weka (5.5: ARFF and XRFF)

0:09:01

Data Mining with Weka (1.4: Building a classifier)

0:07:30

Data Mining with Weka (5.4: Summary)

0:12:42

Advanced Data Mining with Weka (4.3: Using Naive Bayes and JRip)

0:05:22

Advanced Data Mining with Weka (3.6: Application: Functional MRI Neuroimaging data)

0:07:16

Data Mining with Weka (2.6: Cross-validation results)

0:10:00

Data Mining with Weka (4.6: Ensemble learning)

0:09:30

Data Mining with Weka (3.4: Decision trees)

0:07:03

More Data Mining with Weka (5.3: Learning curves)

0:07:44

Data Mining with Weka (5.3: Data mining and ethics)

0:11:06

Data Mining with Weka (1.2: Exploring the Explorer)

0:09:10

Advanced Data Mining with Weka (3.2: Setting up R with Weka)

0:10:50

More Data Mining with Weka (1.5: The Command Line interface)