| 1. |
10/22 |
Machine Learning Essential – R/Python Hands-on and Theoretical Background |
1. Business Problems and Data Mining/Machine Learning Tasks Set 2. Dimensionality Reduction and Principal Component Analysis 3. Clustering Analysis |
鄒慶士(Ching-Shih Tsou) / Prof. C.-S. (Vince) Tsou, Ph.D., |
| 2. |
10/27 |
Machine Learning Essential – R/Python Hands-on and Theoretical Background |
4. Association Rule Mining 5. k Nearest Neighbors 6. Tree-Based Models (Classification Trees, Regression Trees, and Model Trees incl.) |
鄒慶士(Ching-Shih Tsou) / Prof. C.-S. (Vince) Tsou, Ph.D., |
| 3. |
10/29 |
Machine Learning Essential – R/Python Hands-on and Theoretical Background |
7. Naïve Bayes Classification (text processing incl.) 8. Support Vector Machines 9. Bagging and Boosting |
鄒慶士(Ching-Shih Tsou) / Prof. C.-S. (Vince) Tsou, Ph.D., |
| 4. | 11/3 |
Machine Learning Essential – R/Python Hands-on |
10.Naïve Bayes Classification (text processing incl.) 11.Support Vector Machines 12.Ensemble Learning: Bagging and Boosting |
鄒慶士(Ching-Shih Tsou) / Prof. C.-S. (Vince) Tsou, Ph.D., |