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山东大学计算机学院机器学习课程笔记

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// repository documentation

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## About

> 山东大学计算机学院2021-2022机器学习笔记，总结了考试范围内的知识点

## Download & Read

```shell
git clone https://github.com/PTYin/ml-basics.git
```
- Strongly recommend you to open markdown notes in [Typora](https://typora.io/).

## Contents
- [x] Linear Regression [[Markdown](src/Regression.md)] [[PDF](pdf/Regression.pdf)]
- [x] Logistic Regression [[Markdown](src/Logistic.md)] [[PDF](pdf/Logistic.pdf)]
- [x] Bayesian Statistics and Regularization [[Markdown](src/Regularization.md)] [[PDF](pdf/Regularization.pdf)]
- [x] Gaussian Discriminant Analysis, Naive Bayes and EM Algorithm [[Markdown](src/NaiveBayes.md)] [[PDF](pdf/NaiveBayes.pdf)]
- [x] Support Vector Machine [[Markdown](src/SVM.md)] [[PDF](pdf/SVM.pdf)]
- [x] K-Means [[Markdown](src/KMeans.md)] [[PDF](pdf/KMeans.pdf)]
- [x] Factor Analysis and Principle Component Analysis [[Markdown](src/PCA.md)] [[PDF](pdf/PCA.pdf)]
- [x] Learning Theory [[Markdown](src/LearningTheory.md)] [[PDF](pdf/LearningTheory.pdf)]

## QA

- [x] Naive Bayes [[Markdown](src/questions/NaiveBayes.md)] [[PDF](pdf/questions/NaiveBayes.pdf)]

## Appendix

- [x] Matrix Calculus [[Markdown](src/appendix/MatrixCalculus.md)] [[PDF](pdf/appendix/MatrixCalculus.pdf)]
- [x] 矩阵求导 [[Markdown](src/appendix/矩阵求导.md)] [[PDF](pdf/appendix/矩阵求导.pdf)]
- [x] Optimization [[Markdown](src/appendix/Optimization.md)] [[PDF](pdf/appendix/Optimization.pdf)]

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