├── .gitignore ├── .vscode └── settings.json ├── LICENSE ├── README.md ├── docs ├── .nojekyll ├── README.md ├── _sidebar.md ├── index.html ├── resources │ ├── Book.jpg │ └── qrcode.jpeg ├── template.md ├── 第10章 循环神经网络 │ ├── ch10.md │ └── images │ │ ├── 01.png │ │ ├── 02.png │ │ ├── 03.png │ │ └── 04.png ├── 第11章 支持向量机 │ ├── ch11.md │ └── images │ │ ├── output_1.png │ │ ├── output_2.png │ │ ├── output_3.png │ │ ├── output_4.pdf │ │ └── output_4.png ├── 第12章 决策树 │ ├── ch12.md │ └── images │ │ ├── ch12_21_11.png │ │ ├── ch12_21_2.png │ │ ├── ch12_21_5.png │ │ └── ch12_21_8.png ├── 第13章 集成学习与梯度提升决策树 │ ├── ch13.md │ └── image │ │ ├── 1.png │ │ └── 2.png ├── 第14章 k均值聚类 │ ├── ch14.md │ └── images │ │ ├── output_1.png │ │ ├── output_10.png │ │ ├── output_2.png │ │ ├── output_3.png │ │ ├── output_4.png │ │ ├── output_5.png │ │ ├── output_6.png │ │ ├── output_7.png │ │ ├── output_8.png │ │ └── output_9.png ├── 第15章 主成分分析 │ ├── ch15.md │ └── images │ │ ├── ch15_10_0.png │ │ ├── ch15_11_0.png │ │ ├── ch15_12_0.png │ │ └── ch15_4_0.png ├── 第16章 概率图模型 │ └── ch16.md ├── 第17章 EM算法 │ ├── ch17.md │ └── images │ │ ├── ch17_16_0.png │ │ ├── ch17_19_1.png │ │ ├── ch17_19_3.png │ │ ├── ch17_19_5.png │ │ └── ch17_19_7.png ├── 第18章 自动编码器 │ ├── ch18.md │ └── image │ │ ├── 自动编码器_10_1.png │ │ ├── 自动编码器_11_0.png │ │ ├── 自动编码器_15_1.png │ │ ├── 自动编码器_17_1.png │ │ ├── 自动编码器_17_10.png │ │ ├── 自动编码器_17_12.png │ │ ├── 自动编码器_17_14.png │ │ ├── 自动编码器_17_16.png │ │ ├── 自动编码器_17_18.png │ │ ├── 自动编码器_17_2.png │ │ ├── 自动编码器_17_20.png │ │ ├── 自动编码器_17_4.png │ │ ├── 自动编码器_17_6.png │ │ ├── 自动编码器_17_8.png │ │ ├── 自动编码器_7_1.png │ │ ├── 自动编码器_7_11.png │ │ ├── 自动编码器_7_13.png │ │ ├── 自动编码器_7_15.png │ │ ├── 自动编码器_7_3.png │ │ ├── 自动编码器_7_5.png │ │ ├── 自动编码器_7_7.png │ │ └── 自动编码器_7_9.png ├── 第2章 机器学习的数学基础 │ ├── ch02.md │ └── images │ │ ├── ch02_19_1.png │ │ └── ch02_30_0.png ├── 第3章 k近邻算法 │ ├── ch03.md │ └── images │ │ ├── 00.png │ │ ├── 01.png │ │ ├── 02.png │ │ ├── 03.png │ │ ├── 04.png │ │ ├── 05.png │ │ ├── 06.png │ │ ├── 07.png │ │ ├── 08.png │ │ ├── 09.png │ │ ├── 10.png │ │ ├── 11.png │ │ ├── 12.png │ │ ├── 13.png │ │ ├── 14.png │ │ └── 15.png ├── 第4章 线性回归 │ ├── ch04.md │ └── images │ │ ├── ch04_15_1.png │ │ ├── ch04_18_0.png │ │ ├── ch04_19_0.png │ │ ├── ch04_21_0.png │ │ ├── ch04_22_0.png │ │ ├── ch04_24_0.png │ │ ├── ch04_25_0.png │ │ └── ch04_29_0.png ├── 第5章 机器学习的基本思想 │ ├── ch05.md │ └── images │ │ └── machine_img1.png ├── 第6章 逻辑斯谛回归 │ ├── ch06.md │ └── images │ │ ├── ch06_18_1.png │ │ └── ch06_28_1.png ├── 第7章 双线性模型 │ ├── ch07.md │ └── images │ │ ├── ch07_20_1.png │ │ ├── ch07_25_32.png │ │ └── ch07_26_0.png ├── 第8章 神经网络与多层感知机 │ ├── ch08.md │ └── images │ │ ├── ch08_23_1.png │ │ └── ch08_25_1.png └── 第9章 卷积神经网络 │ ├── ch09.md │ └── images │ ├── ch09_17_11.png │ ├── ch09_17_14.png │ ├── ch09_17_2.png │ ├── ch09_17_5.png │ ├── ch09_17_8.png │ └── ch09_21_2.png ├── image ├── Book.jpg └── qrcode.jpeg └── notebooks ├── template.ipynb ├── 第10章 循环神经网络 ├── ch10.ipynb └── sindata_1000.csv ├── 第11章 支持向量机 ├── ch11.ipynb ├── ch11_files │ ├── ch11_17_0.png │ ├── ch11_18_3.png │ ├── ch11_28_1.png │ └── ch11_29_9.png ├── linear.csv └── spiral.csv ├── 第12章 决策树 ├── ch12.ipynb └── titanic │ ├── gender_submission.csv │ ├── test.csv │ └── train.csv ├── 第13章 集成学习与梯度提升决策树 └── ch13.ipynb ├── 第14章 k均值聚类 ├── ch14.ipynb └── kmeans_data.csv ├── 第15章 主成分分析 ├── PCA_dataset.csv └── ch15.ipynb ├── 第16章 概率图模型 ├── ch16.ipynb ├── noisyimg.jpg └── origimg.jpg ├── 第17章 EM算法 ├── ch17.ipynb └── sindata.csv ├── 第18章 自动编码器 └── ch18.ipynb ├── 第2章 机器学习的数学基础 └── ch02.ipynb ├── 第3章 k近邻算法 ├── ch03.ipynb ├── images │ ├── input.jpg │ ├── style.jpg │ └── vangogh │ │ ├── 00001.jpg │ │ ├── 00002.jpg │ │ ├── 00003.jpg │ │ ├── 00004.jpg │ │ ├── 00005.jpg │ │ ├── 00006.jpg │ │ ├── 00007.jpg │ │ ├── 00008.jpg │ │ ├── 00009.jpg │ │ └── 00010.jpg ├── mnist_x └── mnist_y ├── 第4章 线性回归 ├── USA_Housing.csv └── ch04.ipynb ├── 第5章 机器学习的基本思想 └── ch05.ipynb ├── 第6章 逻辑斯谛回归 ├── ch06.ipynb └── lr_dataset.csv ├── 第7章 双线性模型 ├── 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