These are my review notes and lab codes of Machine-Learnring Given by Prof. Muhan Zhang from Peking University in 2023 Fall Semester.
Note
Review notes are about math basis of basic machine learning methods. Because it was written during the review period, some math details were omitted and some of the chapters were unfinished.
The specific machine-learning methods inclued:
- Linear Regression;
- Logistic Regression；
- Support Vector Machine;
- Representer Therom(to be done)；
- Learning Therom(generalization error and VC demension,to be done);
- Gaussian Process Regression;
- Ensemble Learning(bagging and boosting,additive model)
- Unsupervised Learning(PCA,K-means)
- Generative Model(Mixture of Gaussian, EM-algorithm, varitational auto-encoder)
Lab codes are the about implement the machine methods all by yourself. Methods include LR,Logistic,SVM,AdaBoost,Decision Making Tree(with information gain or Gini Index),KNN,AE,VAE.
Warning
Unauthorized reproduction and plagiarism are not allowed without the author's permission