1、机器学习概念
1.1 机器学习是什么
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208152013249-183458329.png)
1.2 机器学习开端
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208152219842-865635012.png)
1.3 机器学习定义
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208152243612-1002728979.png)
1.4 机器学习过程
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208152320291-784595651.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208152330391-1717075580.png)
1.5 示例
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208152342254-1778689492.png)
2、机器学习分类
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208155155335-187049475.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208155446664-1038667770.png)
2.1 无监督学习
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208155519333-817105226.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208155554495-178329083.png)
2.2 监督学习
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208155806160-645775574.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208155817417-658580524.png)
2.3 监督学习应用
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208155837647-1964964276.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208160547082-1163136793.png)
3、监督学习深入介绍
3.1 监督学习三要素
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208164213423-733093015.png)
3.2 监督学习实现步骤
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208164333634-422065467.png)
3.3 监督学习过程示例
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208164549168-135603772.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208164602577-1034063623.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208164613927-1094166065.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208164626009-1662663650.png)
3.4 模型评估策略
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208165023159-1715678824.png)
3.5 训练集和测试集
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208165106411-749289518.png)
3.6 损失函数
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208165230550-1197068751.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208165242227-1224664977.png)
3.7 经验风险
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208165337858-1988764591.png)
3.8 训练误差和测试误差
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208165459540-718467676.png)
3.9 过拟合和欠拟合
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208165545872-622930492.png)
欠拟合
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208165743326-860491046.png)
过拟合
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208165813324-1265247723.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208165826259-800679215.png)
3.10 模型的选择
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208170401985-1289337925.png)
3.11 正则化
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208170432544-285495118.png)
3.12 奥卡姆剃刀
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208170540581-511153598.png)
3.13 交叉验证
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208170936838-984347035.png)
3.14 分类和回归
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208171023726-410915523.png)
分类问题
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208171118138-901411254.png)
精确率和召回率
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208171157917-1450313153.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208171244023-926543783.png)
回归问题
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208171418485-1083063554.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208171430723-537646168.png)
3.15 模型求解算法
梯度下降算法
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208171741434-82884547.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208171806617-852570379.png)
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208171823786-873960202.png)
牛顿法和拟牛顿法
![](https://img2020.cnblogs.com/blog/1267983/202102/1267983-20210208171913639-385301854.png)
posted @
2021-02-08 17:19
勤奋的园
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