機器學習
Machine Learning
| 節 | 週四 |
|---|---|
3 10:10–11:00 | 機器學習 EC122（光復） 2 節連堂 |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
* Note: Due to COVID19, please use this link for the online course before you get registered in the class: https://meet.google.com/hgt-uhxc-mix (1) To build big picture on machine learning field and equip with the ability of implementation machine learning techniques. This course will introduce the theory behind the techniques, so a great deal of time will spend on the mathematics foundation. (2) To understand the properties of different learning algorithms and learn how to use, when to use, which to use, under different scenarios.
Calculus, Probability, Statistics, Linear Algebra, Introduction of Machine learning or equivelent
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Involvement (10%), homework (30%) mid term (30%), final (30%)
Probability and information theory
Basics of Machine learning, Shannon Entropy, Bayes' theorem, Naive Bayes classifier
- 講授：
- 6
Regression and classification
Maximum likelihood, SSE, Linear regression, BIC, Logistic regression, overfitting / regularization (Ridge and Lasso), model selection
- 講授：
- 6
Dimension reduction and feature extraction
SVD, FFT, PCA and NMF
- 講授：
- 6
Distribution and Statistics
Gaussian integral, Central limit theory, Gaussian distribution, Moments of distribution, moment generation function
- 講授：
- 6
Kernel methods
Kernel methods, Gaussian Process, Support Vector Machine
- 講授：
- 6
Generative Models - Clustering
K-Means, Kernel K-Means, Spectral Clustering, DBSCAN, Hierarchical Clustering
- 講授：
- 6
Generative Models - Dimensionality Reduction
PCA, Kernel PCA, LDA, IsoMap, LLE, Laplacian Eigenmap, ICA, t-SNE
- 講授：
- 6
Generative Models - Graphical Models
Directed Graph (Bayesian Networks), Undirected Graph (Markov Random Fields), Factor Graph / Belief Propagation, HMM, Sampling
- 講授：
- 6
| 週次 | 主題 |
|---|---|
| 第 1 週 | 2024-09-05(四) |
| 第 2 週 | 2024-09-12(四) |
| 第 3 週 | 2024-09-19(四) |
| 第 4 週 | 2024-09-26(四) |
| 第 5 週 | 2024-10-03(四) |
| 第 6 週 | 2024-10-10(四) |
| 第 7 週 | 2024-10-17(四) |
| 第 8 週 | 2024-10-24(四) |
| 第 9 週 | 2024-10-31(四) |
| 第 10 週 | 2024-11-07(四) |
| 第 11 週 | 2024-11-14(四) |
| 第 12 週 | 2024-11-21(四) |
| 第 13 週 | 2024-11-28(四) |
| 第 14 週 | 2024-12-05(四) |
| 第 15 週 | 2024-12-12(四) |
| 第 16 週 | 2024-12-19(四) |
[1] Christopher Bishop, Pattern Recognition and Machine Learning, Springer, 2007 [2] A. Smola and S.V.N. Vishwanathan, Introduction to Machine Learning, Cambridge University Press, Oct. 2010
- 地點
- office
- 時間
- TBA
- 聯絡方式