目录
├─1.Jupyter Notebook 基础
├─2.kNN-k邻近算法
├─3.线性回归法
├─4.梯度下降法
├─5.PCA与梯度上升法
├─6.多项式回归与模型泛化
├─7.逻辑回归
├─8.评价分类结果
├─9.支撑向量机 SVM
├─10.决策树
└─11.集成学习和随机森林
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机器学习算法实践
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