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Machine Learning 102 Workshop

This is a training on Machine Learning with R for the Big Data and Analytics course, the S P Jain School of Global Management, Mumbai, India, 30 May - 5 June 2016.

Contents of Training

Unsupervised Learning – I : Cluster Analysis
​1. ​Basic Concepts
​2. ​Partitioning Methods
     2.1. K-means
     2.2. K-medoids
3. Hierarchical Methods
     3.1. Diana
4. Density based Methods
     4.1. DBSCAN
5. Evaluation of Clustering
6. Applications with real world problems
 
Unsupervised Learning- II :  Associations & Correlations
1. Basic Concepts
2. Frequent Itemset Mining Methods
     2.1. Apriori
     2.2. Improving the Efficiency of Apriori
     2.3. FPGrowth
     2.4. ECLAT: Frequent Pattern Mining with  Vertical Data Format
3. Pattern Evaluation Methods
4. Applications with real world problems

Slides

Software and Datasets

Some software/tools and datasets needed for the training as below.

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Yanchang Zhao,
May 27, 2016, 5:15 AM
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Yanchang Zhao,
May 27, 2016, 5:11 AM
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Yanchang Zhao,
May 27, 2016, 5:16 AM
Ċ
Yanchang Zhao,
May 27, 2016, 5:16 AM
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Yanchang Zhao,
May 23, 2016, 5:23 AM
ą
Yanchang Zhao,
Jul 31, 2016, 6:05 AM
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Yanchang Zhao,
Jul 31, 2016, 6:05 AM
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Yanchang Zhao,
Jul 31, 2016, 6:06 AM
ą
Yanchang Zhao,
Jul 31, 2016, 6:06 AM
ą
Yanchang Zhao,
Jul 31, 2016, 6:07 AM