BIL 542 Veri Madenciliği ve Uygulamaları |
| Lecture Slides and Notes |
| Lecture | Lecture Topic | |
| Week 1 | - Introduction - Ch 1 (ppt) | |
| Week 2 | - Getting to Know Your Data - Ch 2 (ppt) | |
| Week 3 | - Data Preprocessing - Ch 3 (ppt) | |
| Week 4 |
- Data Warehousing and On-line Analytical Processing - Ch 4 (ppt) - Data Cube Technology - Skipped - Ch 5 (ppt) |
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| Week 5 |
- Mining Frequent Patterns, Association and Correlations: Basic Concepts and Methods - Ch 6 (ppt) - Advanced Pattern Mining - Skipped - Ch 7 (ppt) |
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| Week 6 |
- Classification and Prediction : Introduction - Ch 8 (ppt) - Classification : Decision Tree Induction - Ch 8 (ppt) - Classification : Bayesian Classification - Ch8 (ppt) |
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| Week 7 |
Classification: SVM (Support Vector Machines) (ppt) Classification: Other Classification Methods Ch 8 (ppt) |
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| Week 8 |
Classification: Neural Networks (NN) History - Ch8 (ppt) Classification: NN and backpropagation - Ch8 (ppt) Classification: Types of NN (ppt) |
Neural Networks Tutorial with Java Applet (html) Matlab - Neural Networks Toolbox (pdf) |
| Week 9 |
Prediction - Ch 8 (ppt) Classification Accuracy - Ch 8 (ppt) |
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| Week 10 |
Clustering : Introduction - Ch 10 (ppt) Clustering: Partitioning Methods - Ch 10 (ppt) |
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| Week 11 |
Clustering: Hierarchical Methods - Ch 10 (ppt) Clustering: Advanced Methods - Skipped- Ch 11 (ppt) |
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| Week 12 |
Outlier Analysis - Ch 12 (ppt) Data Mining Trends and Reseach Fronties - Ch 13 (ppt) |
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Data Mining Resources:
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Supplementary Readings from JHan (HTML)
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Homeworks & Projects |