面试知识点汇总

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

• https://zhuanlan.zhihu.com/p/43827793

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

3. 算法工程师面试常见问题

• https://blog.csdn.net/gzj_1101/article/details/79514902
• 深度学习面试知识点汇总 https://oldpan.me/archives/deep-learning-knowledge