| Week |
Course Content |
| Week 1 |
Formal Model
Perceptron
|
| Week 2 |
Formal Model
Perceptron |
| Week 3 |
Formal Model
Perceptron |
| Week 4 |
AdaLine and Gradient Descent
Realizability Assumption
Sample Complexity |
| Week 5 |
AdaLine and Gradient Descent
Realizability Assumption
Sample Complexity |
| Week 6 |
AdaLine and Gradient Descent
Realizability Assumption
Sample Complexity |
| Week 7 |
Probably Approximately Correct (PAC) Learning
Agonostic PAC Learning
Uniform Convergence |
| Week 8 |
Probably Approximately Correct (PAC) Learning
Agonostic PAC Learning
Uniform Convergence |
| Week 9 |
Probably Approximately Correct (PAC) Learning
Agonostic PAC Learning
Uniform Convergence |
| Week 10 |
General Linear Model
Logistic Regression
A General Flow of Learning Process
Bias-Variance TradeOff |
| Week 11 |
General Linear Model
Logistic Regression
A General Flow of Learning Process
Bias-Variance TradeOff |
| Week 12 |
General Linear Model
Logistic Regression
A General Flow of Learning Process
Bias-Variance TradeOff |
| Week 13 |
General Linear Model
Logistic Regression
A General Flow of Learning Process
Bias-Variance TradeOff |
| Week 14 |
報告:教育數據的搜尋與理解 |
| Week 15 |
報告:教育數據的搜尋與理解 |
| Week 16 |
報告:教育數據的搜尋與理解
報告:教育數據的搜尋與理解
報告:教育數據的搜尋與理解 |
self-directed learning |
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