GitHub - AnXinrui/Machine_Learning-2: 西瓜书，sklearn源码，李航统计学，机器学习实战

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西瓜书，sklearn源码，李航统计学，机器学习实战

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
Scripts		Scripts
files		files
img		img
01-数据集划分-留出法及代码实现.ipynb		01-数据集划分-留出法及代码实现.ipynb
02-数据划分-K折及代码实现.ipynb		02-数据划分-K折及代码实现.ipynb
03-数据划分-自助法代码实现.ipynb		03-数据划分-自助法代码实现.ipynb
04-混淆矩阵的实现.ipynb		04-混淆矩阵的实现.ipynb
05-精准率和召回率实现.ipynb		05-精准率和召回率实现.ipynb
06-假设检验原理及代码实现.ipynb		06-假设检验原理及代码实现.ipynb
07-线性回归原理-评价标准-假设检验及代码实现.ipynb		07-线性回归原理-评价标准-假设检验及代码实现.ipynb
08-多元线性回归.ipynb		08-多元线性回归.ipynb
09-梯度下降原理及代码实现.ipynb		09-梯度下降原理及代码实现.ipynb
10-逻辑回归中sigmoid和损失函数原理.ipynb		10-逻辑回归中sigmoid和损失函数原理.ipynb
11-逻辑回归代码实现.ipynb		11-逻辑回归代码实现.ipynb
12-精准率与召回率的调节.ipynb		12-精准率与召回率的调节.ipynb
13-ROC曲线的实现.ipynb		13-ROC曲线的实现.ipynb
14-信息熵和基尼系数的初步探索.ipynb		14-信息熵和基尼系数的初步探索.ipynb
15-基于信息熵的决策划分.ipynb		15-基于信息熵的决策划分.ipynb
16-基于基尼系数的划分.ipynb		16-基于基尼系数的划分.ipynb
17-误差逆向传播公式推导.ipynb		17-误差逆向传播公式推导.ipynb
18-误差逆向传播的代码实现.ipynb		18-误差逆向传播的代码实现.ipynb
19-Hard Margin SVM.ipynb		19-Hard Margin SVM.ipynb
20-Soft Margin SVM.ipynb		20-Soft Margin SVM.ipynb
21-SVM中的核函数.ipynb		21-SVM中的核函数.ipynb
22-SMO算法及原生代码实现（机器学习实战源码）.ipynb		22-SMO算法及原生代码实现（机器学习实战源码）.ipynb
23-K-means代码实现.ipynb		23-K-means代码实现.ipynb
24-Calinski-Harabasz Index.ipynb		24-Calinski-Harabasz Index.ipynb
25-矩阵奇异分解原理.ipynb		25-矩阵奇异分解原理.ipynb
26-PCA-使用矩阵奇异分解.ipynb		26-PCA-使用矩阵奇异分解.ipynb
27-KNN算法实现.ipynb		27-KNN算法实现.ipynb
28-深度学习之原理及mnist分类.ipynb		28-深度学习之原理及mnist分类.ipynb
29-使用keras进行实现猫狗分类.ipynb		29-使用keras进行实现猫狗分类.ipynb
cats_and_dogs_small_1.h5		cats_and_dogs_small_1.h5

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