https://github.com/erectbranch/kmooc-advanced-ml
Advanced machine learning | K-MOOC • 2023
https://github.com/erectbranch/kmooc-advanced-ml
bayesian-network genetic-algorithm graph-model hidden-markov-model k-mooc kernel-method machine-learning
Last synced: 3 days ago
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Advanced machine learning | K-MOOC • 2023
- Host: GitHub
- URL: https://github.com/erectbranch/kmooc-advanced-ml
- Owner: erectbranch
- Created: 2025-11-28T05:24:12.000Z (5 months ago)
- Default Branch: master
- Last Pushed: 2026-04-10T02:11:12.000Z (17 days ago)
- Last Synced: 2026-04-10T03:24:36.990Z (17 days ago)
- Topics: bayesian-network, genetic-algorithm, graph-model, hidden-markov-model, k-mooc, kernel-method, machine-learning
- Homepage: https://erectbranch.github.io/#/kmooc-advanced-ml/notes/
- Size: 7.7 MB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
Advanced machine learning
K-MOOC • 2023
Instructor : Jee-Hyong Lee(Professor, Sungkyunkwan University)
Lecture notes for courses [Advanced machine learning](https://www.kmooc.kr/view/course/detail/5928?tm=20251016130104) (딥러닝 시대에도 필요한 고급기계학습).
## Lecture Notes
- [Graphical Model(GM)](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec01)
> Probability, Conditional Probability, Bayesian Reasoning, Independence
- [Bayesian Network Overview](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec02)
> Probabilistic Reasoning, Bayesian Network, d-separation
- [Inference in Bayesian Networks](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec03)
> Inference in Bayesian Networks, Inference in Polytrees
- [Hidden Markov Model Overview](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec04)
> Markov Model, Hidden Markov Model
- [Estimation of HMM](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec05)
> Baum-Welch Algorithm, Viterbi Algorithm
- [Non-Linear SVM](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec09)
> Non-Linear SVM, Kernel Trick
- [Random Forest](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec10)
> Bagging, Random Forest, Out-Of-Bag Error
- [Gaussian Process](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec12)
> Gaussian Distribution, Covariance Matrix, Gaussian Process
- [Singular Value Decomposition(SVD)](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec13/summary01)
> Linear Transformation, eigenvalue, eigenvector, Singular Value Decomposition
- [Matrix Factorization](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec13/summary02)
> Matrix Factorization Variations
- [Gaussian Mixture Model(GMM)](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec14/summary01)
> Gaussian Mixture Model
- [Expectation-Maximization(EM) Algorithm](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec14/summary02)
> Expectation-Maximization Algorithm, Jensen's Inequality, GMM by EM Algorithm
## :mag: Syllabus
### 1. Graphical Model
### 2. Bayesian Network
### 3. Hidden Markov Model
### 4. Genetic Algorithm
### 5. Support Vector Machine
### 6. Random Forest
### 7. Adaboost
### 8. Gaussian Process
### 9. Matrix Factorization
### 10. Gaussian Mixture Model