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https://patch-diff.githubusercontent.com/Neil03/MachineLearning#机器学习
第 1 章: 机器学习基础https://github.com/apachecn/MachineLearning/blob/master/docs/1.机器学习基础.md
@毛红动https://github.com/ElmaDavies
第 2 章: KNN 近邻算法https://github.com/apachecn/MachineLearning/blob/master/docs/2.k-近邻算法.md
@尤永江https://github.com/youyj521
第 3 章: 决策树https://github.com/apachecn/MachineLearning/blob/master/docs/3.决策树.md
@景涛https://github.com/jingwangfei
第 4 章: 朴素贝叶斯https://github.com/apachecn/MachineLearning/blob/master/docs/4.朴素贝叶斯.md
@wnma3mzhttps://github.com/wnma3mz
@分析https://github.com/kailian
第 5 章: Logistic回归https://github.com/apachecn/MachineLearning/blob/master/docs/5.Logistic回归.md
@微光同尘https://github.com/DataMonk2017
第 6 章: SVM 支持向量机https://github.com/apachecn/MachineLearning/blob/master/docs/6.支持向量机.md
@王德红https://github.com/VPrincekin
第 7 章: 集成方法(随机森林和 AdaBoost)https://github.com/apachecn/MachineLearning/blob/master/docs/7.集成方法-随机森林和AdaBoost.md
@片刻https://github.com/jiangzhonglian
第 8 章: 回归https://github.com/apachecn/MachineLearning/blob/master/docs/8.回归.md
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第 9 章: 树回归https://github.com/apachecn/MachineLearning/blob/master/docs/9.树回归.md
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第 10 章: K-Means 聚类https://github.com/apachecn/MachineLearning/blob/master/docs/10.k-means聚类.md
@徐昭清https://github.com/xuzhaoqing
第 11 章: 利用 Apriori 算法进行关联分析https://github.com/apachecn/MachineLearning/blob/master/docs/11.使用Apriori算法进行关联分析.md
@刘海飞https://github.com/WindZQ
第 12 章: FP-growth 高效发现频繁项集https://github.com/apachecn/MachineLearning/blob/master/docs/12.使用FP-growth算法来高效发现频繁项集.md
@程威https://github.com/mikechengwei
第 13 章: 利用 PCA 来简化数据https://github.com/apachecn/MachineLearning/blob/master/docs/13.利用PCA来简化数据.md
@廖立娟https://github.com/lljuan330
第 14 章: 利用 SVD 来简化数据https://github.com/apachecn/MachineLearning/blob/master/docs/14.利用SVD简化数据.md
@张俊皓https://github.com/marsjhao
第 15 章: 大数据与 MapReducehttps://github.com/apachecn/MachineLearning/blob/master/docs/15.大数据与MapReduce.md
第 16 章: 推荐系统https://github.com/apachecn/MachineLearning/blob/master/docs/16.推荐系统.md
https://patch-diff.githubusercontent.com/Neil03/MachineLearning#深度学习deeplearning--正在更新迭代
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自然语言处理入门介绍https://patch-diff.githubusercontent.com/Neil03/MachineLearning/blob/dev/docs/NLP/1.%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86%E5%85%A5%E9%97%A8%E4%BB%8B%E7%BB%8D.md
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https://patch-diff.githubusercontent.com/Neil03/MachineLearning#第四部分-unit-语言理解与交互技术
UNIT-语言理解与交互技术https://patch-diff.githubusercontent.com/Neil03/MachineLearning/blob/dev/docs/NLP/4.UNIT-%E8%AF%AD%E8%A8%80%E7%90%86%E8%A7%A3%E4%B8%8E%E4%BA%A4%E4%BA%92%E6%8A%80%E6%9C%AF.md
https://patch-diff.githubusercontent.com/Neil03/MachineLearning#网站视频
知乎问答-爆炸啦-机器学习该怎么入门?https://www.zhihu.com/question/20691338/answer/248678328
MachineLearning(机器学习) 学习路线图http://www.apachecn.org/map/145.html
https://patch-diff.githubusercontent.com/Neil03/MachineLearning/blob/dev/images/MainPage/ApacheCN-ML-bilibili-compare.jpg
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《机器学习实战-讨论版》https://space.bilibili.com/97678687/#!/channel/detail?cid=13045
机器学习初学者建议 | ApacheCNhttp://www.apachecn.org/map/179.html
MachineLearning(机器学习) 学习路线图http://www.apachecn.org/map/145.html
@于振梓�https://patch-diff.githubusercontent.com/Neil03/MachineLearning/blob/dev
可汗学院(概率)http://open.163.com/special/Khan/probability.html
可汗学院(统计学)http://open.163.com/special/Khan/khstatistics.html
可汗学院(线性代数)http://open.163.com/special/Khan/linearalgebra.html
http://www.acfun.cn/u/12540256.aspx#page=1
https://space.bilibili.com/97678687/#!/channel/index
http://i.youku.com/apachecn
http://study.163.com/course/courseMain.htm?courseId=1004582003
吴恩达机器学习http://study.163.com/course/courseMain.htm?courseId=1004570029
神经网络和深度学习http://mooc.study.163.com/course/2001281002?tid=2001392029
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