# Machine-Learning-Method_Code **Repository Path**: jaheel/Machine-Learning-Method_Code ## Basic Information - **Project Name**: Machine-Learning-Method_Code - **Description**: 机器学习常见算法理论讲解及其代码实现。文章均为原创文章，代码均为贡献者自己实现。 - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 1 - **Forks**: 0 - **Created**: 2021-10-30 - **Last Updated**: 2022-05-19 ## Categories & Tags **Categories**: Uncategorized **Tags**: Machine-learning ## README # Machine Learning [![MIT license](https://camo.githubusercontent.com/3f7996bf7bd441deb7199c498aaa835164dee8da/68747470733a2f2f696d672e736869656c64732e696f2f6475622f6c2f766962652d642e737667)](https://github.com/lawlite19/MachineLearning_Python/blob/master/LICENSE) 该库用于常见机器学习算法的理论讲解及其代码实现。文章均为原创文章，代码均为贡献者自己实现。 | Method | Theory | Code | Manager | e-mail | | ------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------ | ------------------------- | | 0 绪论(Introduction) | [Theory](/0_Introduction) | | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 0.1 性能度量(Performance Metrics) | [Theory](/0_Introduction/Performance_Metrics) | | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 1 线性回归(Linear Regression) | | [Code](/1_Linear_regression/Code) | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 2 逻辑回归(Logistics Regression) | [Theory](/2_Logistic_regression/Theory) | | [@Aristotle-wu](https://github.com/Aristotle-wu) | wuweixuan2017@outlook.com | | 3 决策树(Decision Tree) | [Theory](/3_Decision_Tree/Theory) | | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 4 XGBoost | [Theory](/4_XGBoost/Theory) | | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 5 支持向量机(Support Vector Machine) | [Theory](/5_SVM/Theory) | [Code](/5_SVM/Code) | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 6 贝叶斯(Bayes) | [Theory](/6_Bayes/Theory) | [Code](/6_Bayes/Code) | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 7 神经网络(Neural Network) | [Theory](/7_Neural_Network/Theory) | [Code](/7_Neural_Network/Code) | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 7.1 Dropout | [Theory](/7_Neural_Network/c3_dropout) | | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 8 聚类(Clustering) | [Theory](/8_Clustering/Theory) | | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 9 降维与度量学习 | | | | | | 9.1 kNN | [Theory](/9_Dimensionality_reduction_and_metric_learning/Theory/kNN) | [Code](/9_Dimensionality_reduction_and_metric_learning/Code/kNN) | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 9.2 PCA | | [Code](/9_Dimensionality_reduction_and_metric_learning/Code/PCA) | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 9.3 MDS | | [Code](/9_Dimensionality_reduction_and_metric_learning/Code/MDS) | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 9.4 Isomap | | [Code](/9_Dimensionality_reduction_and_metric_learning/Code/Isomap) | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 10 集成学习(ensemble learning) | [Theory](/10_Emsemble_learning/Theory/Ensemble_learning) | | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 10.1 Boosting | [Theory](/10_Ensemble_learning/Theory/Boosting) | | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 10.2 Bagging and RF(随机森林) | [Theory](/10_Ensemble_learning/Theory/Bagging_and_RF) | | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 11 特征选择与稀疏学习 | [Theory](/11_Feature_selection_and_sparse_learning/Theory) | | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 12 计算学习理论 | [Theory](/12_Computational_learning_theory/Theory) | | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | | 13 卷积神经网络 | | [Code](/13_CNN/Code/) | [@Alex](https://github.com/jaheel) | xufanxin86@gmail.com | # Appendix 欢迎关注微信公众号：繁星的人工智能厨房 ![微信公众号二维码](images/微信公众号二维码.png)