> For the complete documentation index, see [llms.txt](https://luweikxy.gitbook.io/machine-learning-notes/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://luweikxy.gitbook.io/machine-learning-notes/machine-learning-algorithm-summary.md).

# 机器学习算法总结

* [返回顶层目录](https://luweikxy.gitbook.io/machine-learning-notes/pages/-LpO5vE88qYwjk5WM_Qf#目录)

[各种机器学习的应用场景分别是什么？例如，k近邻,贝叶斯，决策树，svm，逻辑斯蒂回归和最大熵模型。](https://www.zhihu.com/question/26726794/answer/33958453)

各种机器学习的应用场景分别是什么？例如，k近邻,贝叶斯，决策树，svm，逻辑斯蒂回归和最大熵模型。

<https://www.zhihu.com/question/26726794/answer/151282052>

机器学习算法集锦：从贝叶斯到深度学习及各自优缺点

<https://zhuanlan.zhihu.com/p/25327755>

[最详细的机器学习算法优缺点综述](https://mp.weixin.qq.com/s?__biz=MzA4NzE1NzYyMw==\&mid=2247497586\&idx=2\&sn=5c6dd39c1f0a86ba7c6d0ff77f25fbaa\&chksm=903f096aa748807cf84164d1b2f305990cdd852c30c5b313a6e68d06c5d3828d58e13b3c83e1\&mpshare=1\&scene=1\&srcid=0510yNikhsDGqKQIsLP7R2Wx#rd)

[常用的机器学习算法比较？](https://www.zhihu.com/question/27306416)

[常用机器学习常用算法优点及缺点总结](https://zhuanlan.zhihu.com/p/36928215)

[RF、GBDT、XGBoost面试级整理](https://mp.weixin.qq.com/s?__biz=MzA3MDg0MjgxNQ==\&mid=2652392468\&idx=1\&sn=ba74a18ca224881beed829153832cf71\&chksm=84da4cc4b3adc5d2b71ca4bae12d317bc5c1f1f62917553515c2ce5bba08631bb4846402788a\&mpshare=1\&scene=1\&srcid=0322kvtbkBdvmHp5mXdT19jJ#rd)

[机器学习算法优缺点综述](https://zhuanlan.zhihu.com/p/37015599)

[用一句话总结常用的机器学习算法](https://mp.weixin.qq.com/s?__biz=MzU4MjQ3MDkwNA==\&mid=2247484859\&idx=1\&sn=2c4db22fb538953a62a90983e3e1f99d\&chksm=fdb6982ccac1113a82e92be325bb07a947d54090274654375f3b50e11e1abd809fb7358bde16\&scene=0#rd)


---

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