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\u003cp align=\"center\"\u003eAdvanced machine learning\u003c/p\u003e\n  \u003ca href=\"https://www.kmooc.kr/view/course/detail/5928?tm=20251016130104\"\u003e\n    \u003cimg width=\"50%\" src=\"cover.jpg\" /\u003e\n  \u003c/a\u003e\n\u003c/h1\u003e\n  \n\u003cb\u003eK-MOOC • 2023\u003c/b\u003e\n\u003cbr\u003e\nInstructor : Jee-Hyong Lee(Professor, Sungkyunkwan University)\n\n\u003c/div\u003e\n\n\u003cbr\u003e\n\nLecture notes for courses [Advanced machine learning](https://www.kmooc.kr/view/course/detail/5928?tm=20251016130104) (딥러닝 시대에도 필요한 고급기계학습).\n\n## Lecture Notes\n\n- [Graphical Model(GM)](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec01)\n\n  \u003e Probability, Conditional Probability, Bayesian Reasoning, Independence\n\n- [Bayesian Network Overview](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec02)\n\n  \u003e Probabilistic Reasoning, Bayesian Network, d-separation\n\n- [Inference in Bayesian Networks](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec03)\n\n  \u003e Inference in Bayesian Networks, Inference in Polytrees\n\n- [Hidden Markov Model Overview](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec04)\n\n  \u003e Markov Model, Hidden Markov Model\n\n- [Estimation of HMM](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec05)\n\n  \u003e Baum-Welch Algorithm, Viterbi Algorithm\n\n- [Non-Linear SVM](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec09)\n\n  \u003e Non-Linear SVM, Kernel Trick\n\n- [Random Forest](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec10)\n\n  \u003e Bagging, Random Forest, Out-Of-Bag Error\n\n- [Gaussian Process](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec12)\n\n  \u003e Gaussian Distribution, Covariance Matrix, Gaussian Process\n\n- [Singular Value Decomposition(SVD)](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec13/summary01)\n\n  \u003e Linear Transformation, eigenvalue, eigenvector, Singular Value Decomposition\n\n- [Matrix Factorization](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec13/summary02)\n\n  \u003e Matrix Factorization Variations\n\n- [Gaussian Mixture Model(GMM)](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec14/summary01)\n\n  \u003e Gaussian Mixture Model\n\n- [Expectation-Maximization(EM) Algorithm](https://github.com/erectbranch/kmooc-advanced-ml/tree/master/lec14/summary02)\n\n  \u003e Expectation-Maximization Algorithm, Jensen's Inequality, GMM by EM Algorithm\n\n## :mag: Syllabus\n\n### 1. Graphical Model\n\n### 2. Bayesian Network\n\n### 3. Hidden Markov Model\n\n### 4. Genetic Algorithm\n\n### 5. Support Vector Machine\n\n### 6. Random Forest\n\n### 7. Adaboost\n\n### 8. Gaussian Process\n\n### 9. Matrix Factorization\n\n### 10. Gaussian Mixture Model","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ferectbranch%2Fkmooc-advanced-ml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ferectbranch%2Fkmooc-advanced-ml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ferectbranch%2Fkmooc-advanced-ml/lists"}