| 1. | |
Basic Probability Theory | Basic Probability Theory |  |
| 2. | |
Basic Probability Theory | Basic Probability Theory | |
| 3. | |
Bayesian Inference and Decision Theory | Bayesian Inference and Decision Theory | |
| 4. | |
Pattern Recognition and Bayesian Decision Theory | Pattern Recognition and Bayesian Decision Theory | |
|
Logistic-Regression | |
||
| 5. | |
Perceptron and SVM for Pattern recognition | Perceptron and SVM for Pattern recognition | |
| 6. | |
Support Vector Machines | Support Vector Machines | |
|
Support Vector Machines | Support Vector Machines | |
|
| 7. | |
Principle Component Analysis (PCA) | Principle Component Analysis (PCA) | |
| 8. | |
Unsupervised Learning | Unsupervised Learning | |
|
Unsupervised Learning | Unsupervised Learning | |
|
|
Unsupervised Learning | Unsupervised Learning | |
|
| 9. | |
Gaussian mixture model | Gaussian mixture model | |
| 10. | |
Deep neural networks | Deep neural networks | |
| 11. | |
Dynamic time warping | Dynamic time warping | |
| 12. | |
Recurrent Neural Networks | Recurrent Neural Networks | |
대구광역시 동구 동내로 64(동내동 1119) 우)41061
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