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Title: GitHub - DeepInDeeper/MachineLearningZeroToALL: 机器学习算法(python)

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Description: 机器学习算法(python). Contribute to DeepInDeeper/MachineLearningZeroToALL development by creating an account on GitHub.

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MIT license	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/LICENSE
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1-LinearRegression	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/1-LinearRegression
1-LinearRegression	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/1-LinearRegression
2-LogisticRegression	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/2-LogisticRegression
2-LogisticRegression	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/2-LogisticRegression
3-NeuralNetwok	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/3-NeuralNetwok
3-NeuralNetwok	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/3-NeuralNetwok
4-SVM	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/4-SVM
4-SVM	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/4-SVM
5-K-Means	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/5-K-Means
5-K-Means	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/5-K-Means
6-PCA	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/6-PCA
6-PCA	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/6-PCA
7-AnomalyDetection	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/7-AnomalyDetection
7-AnomalyDetection	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/7-AnomalyDetection
8-HMM	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/8-HMM
8-HMM	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/8-HMM
9-NaiveBayer/note	https://github.com/DeepInDeeper/MachineLearningZeroToALL/tree/master/9-NaiveBayer/note
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readme.ipynb	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/readme.ipynb
readme.ipynb	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/readme.ipynb
readme.md	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/readme.md
readme.md	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/readme.md
README	https://github.com/DeepInDeeper/MachineLearningZeroToALL
MIT license	https://github.com/DeepInDeeper/MachineLearningZeroToALL
code	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/code
data	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/data
LSJU机器学习笔记	https://github.com/zlotus/notes-LSJU-machine-learning
这里	http://nbviewer.jupyter.org/github/Peterchenyijie/MachineLearningZeroToALL/blob/master/readme.ipynb
	https://github.com/PeterChenYijie/MachineLearningZeroToALL/blob/master/LICENSE
	https://github.com/DeepInDeeper/MachineLearningZeroToALL#机器学习算法python实现
	https://github.com/DeepInDeeper/MachineLearningZeroToALL#ipynb-学习目录
0 Basic Concept\|基础概念	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/0-BasicConcept
概率论	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/0-BasicConcept/note/probability_theory.ipynb
1 Linear Regression\|线性回归	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/1-LinearRegression
线性回归笔记	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/1-LinearRegression/note
LSJU笔记-监督学习应用	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/1-LinearRegression/note/LSJU_chapter02.ipynb
LSJU笔记-线性模型概率解释、局部加权回归	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/1-LinearRegression/note/LSJU-chapter03_01.ipynb
LSJU笔记-一般线性模型	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/1-LinearRegression/note/LSJU_chapter04.ipynb
笔记	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/1-LinearRegression/note/NOTE-linear_regression.ipynb
线性回归的实现	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/1-LinearRegression/LinearRegression.ipynb
使用sklearn 线性回归	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/1-LinearRegression/LinearRegression_sklearn.ipynb
Mxnet 实现线性回归	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/1-LinearRegression/linear_regression_mxnet.ipynb
2 Logistic Regression\|逻辑回归	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/2-LogisticRegression
逻辑回归笔记	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/2-LogisticRegression/note
LSJU笔记-分类问题、逻辑回归	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/2-LogisticRegression/note/LSJU-chapter03_2.ipynb
逻辑回归笔记	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/2-LogisticRegression/note/NOTE-logistic_regression.ipynb
逻辑回归的实现	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/2-LogisticRegression/LogisticRegression.ipynb
使用sklearn 逻辑回归	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/2-LogisticRegression/LogisticRegression_scikit-learn.ipynb
逻辑回归识别手写数字	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/2-LogisticRegression/LogisticRegression_OneVsAll.ipynb
使用sklearn 逻辑回归识别手写数字	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/2-LogisticRegression/LogisticRegression_OneVsAll_scikit-learn.ipynb
3 Neural Network\|神经网络	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/3-NeuralNetwok
神经网络笔记	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/3-NeuralNetwok/note/NOTE-neural_network.md
神经网络识别手写数字	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/3-NeuralNetwok/NeuralNetwork.ipynb
4 SVM\|支持向量机	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/4-SVM
SVM笔记	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/4-SVM/NOTE-SVM.md
使用sklearn SVM	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/4-SVM/SVM_scikit-learn.ipynb
5 K-Means\|聚类	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/5-K-Means
K-Mean 聚类笔记	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/5-K-Means/LSJU----NOTE-K-Means.ipynb
K-Mean的实现	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/5-K-Means/K-Means.ipynb
使用sklearn K-Means	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/5-K-Means/K-Means-sklearn.ipynb
6 PCA\|主成分分析	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/6-PCA
PCA笔记	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/6-PCA/note/LSJU----NOTE-PCA.ipynb
PCA的实现	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/6-PCA/PCA.ipynb
使用sklearn PCA	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/6-PCA/PCA_sklearn.ipynb
7 Anomaly Detection\|异常检测	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/7-AnomalyDetection
异常检测笔记	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/7-AnomalyDetection/note/NOTE-anomaly_detection.md
异常检测实现	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/7-AnomalyDetection/AnomalyDetection.ipynb
8 HMM\|隐马尔可夫模型	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/8-HMM
马尔科夫决策过程	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/8-HMM/note/LSJU-HMM.ipynb
这里	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/8-HMM/note/sn06.ipynb
9 NaiveBayer\|朴素贝叶斯	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/9-NaiveBayer
笔记	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/9-NaiveBayer/note
LSJU-生成学习算法、高斯判别分布、朴素贝叶斯算法	https://github.com/DeepInDeeper/MachineLearningZeroToALL/blob/master/9-NaiveBayer/note/LSJU-chapter05.ipynb
收藏！机器学习算法优缺点综述	https://mp.weixin.qq.com/s/Xomx6Z_fP1EsnwNEegj5Cw
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