TingNie / Machine Learning In Action
个人使用jupyter notebook整理的peter的《机器学习实战》代码，使其更有层次感，更加连贯，也加了一些自己的修改，以及注释
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Machine-learning-in-action
个人使用jupyter notebook整理的peter的《机器学习实战》代码，使其更有层次感，更加连贯，也根据自己的代码习惯，加了一些自己的修改，以及注释
这是给自己做的笔记，贴出来，也是希望大家一起学习!
注：原版所有代码点击这里 GitHub整理的资源apachecn/MachineLearning
内容包括：
adaBoost文件夹：AdaBoost元算法提高分类性能
apriori文件夹：Apriori算法进行关联分析
bayes文件夹：bayes算法用于垃圾邮件分类
decisionTree文件夹：使用决策树算法，进行数据分类
fp-growth文件夹：FP-growth算法加速发现频繁项集
kmeans文件夹：kmeans + 二分kmeans算法
k-Nearest Neighbor文件夹：k近邻算法 + 数值归一化
logistic文件夹：batch GD + SGD
pca文件夹：pca降维
pca和svd的比较：关于pca和svd的区别和联系，理论参见博客
regress文件夹：线性回归 + 局部加权线性回归 + 岭回归 + 向前逐步回归
regressionTree文件夹：回归树+模型树
svd文件夹：svd降维 + 协同过滤算法进行物品推荐
svm文件夹：简化版smo实现svm(支持向量机)分类器
完结
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