1. LR
- https://zhuanlan.zhihu.com/p/34670728
- https://blog.csdn.net/u010867294/article/details/79138603
- https://blog.csdn.net/weixin_42933718/article/details/88874376
2. 决策树
- https://www.cnblogs.com/liuyingjun/p/10590095.html
- https://blog.csdn.net/Datawhale/article/details/102878758
3.SVM
4. 集成算法
- XGBoost：https://www.cnblogs.com/yanshw/p/10631440.html
- 决策树-GBDT, Xgboost，LGBM https://zhuanlan.zhihu.com/p/91395504
- 深入理解GBDT回归算法https://cloud.tencent.com/developer/article/1529963
- 机器学习算法之LightGBM https://www.biaodianfu.com/lightgbm.html
- XGBoost详解 https://www.jianshu.com/p/ac1c12f3fba1
5. 深度学习
- 梯度消失 https://www.jianshu.com/p/3f35e555d5ba
- 什么是fine-tuning？https://blog.csdn.net/weixin_42137700/article/details/82107208
- 人人都能看懂的GRU https://zhuanlan.zhihu.com/p/32481747
- dropout：让某个神经元以概率p停止工作，其实就是让它的激活函数值以概率p变为0 https://blog.csdn.net/program_developer/article/details/80737724
- Keras关于LSTM的units参数，还是不理解?https://www.zhihu.com/question/64470274/answer/256379387
- 深度学习中的epochs，batch_size，iterations详解https://blog.csdn.net/maweifei/article/details/80722097
https://www.jiqizhixin.com/articles/2017-09-25-3
6. PCA
- 如何理解主元分析（PCA）？https://www.matongxue.com/madocs/1025/
7.kmeans
- K-Means聚类算法原理 https://www.cnblogs.com/pinard/p/6164214.html
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