[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-9826":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":9,"language":9,"languages":9,"totalLinesOfCode":9,"stars":10,"forks":11,"watchers":12,"openIssues":13,"contributorsCount":14,"subscribersCount":14,"size":14,"stars1d":15,"stars7d":15,"stars30d":16,"stars90d":14,"forks30d":14,"starsTrendScore":13,"compositeScore":17,"rankGlobal":9,"rankLanguage":9,"license":9,"archived":18,"fork":18,"defaultBranch":19,"hasWiki":20,"hasPages":18,"topics":21,"createdAt":9,"pushedAt":9,"updatedAt":28,"readmeContent":29,"aiSummary":30,"trendingCount":14,"starSnapshotCount":14,"syncStatus":31,"lastSyncTime":32,"discoverSource":33},9826,"Machine-Learning-Notes","Sophia-11\u002FMachine-Learning-Notes","Sophia-11","周志华《机器学习》手推笔记",null,3776,746,132,3,0,1,8,60.92,false,"master",true,[22,23,24,25,26,27],"algorithms","artificial-intelligence","deep-learning","machine-learning","notes","phd","2026-06-12 04:00:47","### Machine-Learning-Notes(加载图片较慢，请耐心等待,只显示一部分)\n* 如果刷新不出来，可以点击 [神经网络](https:\u002F\u002Fmp.weixin.qq.com\u002Fs\u002FusIVYjffOL6oBUGUDalYLg)  查看笔记大概是什么样子的\n\n* 周志华《机器学习》手推笔记（踏踏实实把公式学习推导一遍）\n\n* by 【计算机视觉联盟】 王博Kings、Sophia\n\n# 手推笔记十六章 214页 A4纸，可直接打印 ！！\n\n*Last updated: 2021\u002F03\u002F13*   **更新完结十六章**\n\n## 公众号【计算机视觉联盟】回复【西瓜书手推笔记】即可获得百度云pdf下载链接\n\n## 后续请大家继续关注另一个重磅笔记： [**深度学习手推笔记**](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FDeepLearningNotes)\n\n## Table of Contents\n- [第一章绪论](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第二章模型评估与选择](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第三章线性模型](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第四章决策树](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第五章神经网络](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第六章支持向量机](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第七章贝叶斯分类器](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第八章集成信息](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第九章聚类](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第十章降维与度量学习](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第十一章特征选择与稀疏学习](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第十二章计算学习理论](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第十三章半监督学习](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第十四章概率图模型](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第十五章规则学习](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n- [第十六章强化学习](https:\u002F\u002Fgithub.com\u002FSophia-11\u002FMachine-Learning-Notes\u002F)\n\n\n## 手推笔记作者简介--王博Kings\n微信号（Kingsplusa）备注：单位\u002F学校+研究方向\n\n985AI博士，CSDN博客专家，华为云享专家\n\n已连载系列《机器学习》西瓜书手推笔记\n\n已完结待更笔记：《深度学习-花书手推笔记》、《无人驾驶手推笔记》、《SLAM 十四讲》\n\n| 下载地址 | 博士私人微信 |\n|:-----------:|:-----------:|\n|![](.\u002FcvQD.jpg)|![](.\u002FKingsplus.jpg)| \n|【计算机视觉联盟】回复【西瓜书手推笔记】即可获得百度云pdf下载链接|985AI博士，CSDN博客专家|\n\n\n## 第一章 绪论\n\n ![image](.\u002Fch1\u002Fch01.png)\n\n## 第二章  模型评估与选择\n| 1 | 2 | 3 |4 |\n|:-----------:|:--------:|:---------:|:---------:|\n|![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F0001_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F0002_%E5%89%AF%E6%9C%AC.jpg)|  ![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F0003_%E5%89%AF%E6%9C%AC.jpg)| \n|![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F0004_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F0005_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F0006_%E5%89%AF%E6%9C%AC.jpg)|  ![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F0007_%E5%89%AF%E6%9C%AC.jpg)| \n|![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F0008_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F0009_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F0010_%E5%89%AF%E6%9C%AC.jpg)|  ![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F0011_%E5%89%AF%E6%9C%AC.jpg)| \n|![](.\u002Fch2\u002F%E6%89%AB%E6%8F%8F0012_%E5%89%AF%E6%9C%AC.jpg)|--by 王博Kings||| \n\n\n\n## 第三章  线性模型\n| 1 | 2 | 3 |4 |\n|:-----------:|:--------:|:---------:|:---------:|\n|![](.\u002Fch3\u002F%E6%89%AB%E6%8F%8F0014_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch3\u002F%E6%89%AB%E6%8F%8F0015_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch3\u002F%E6%89%AB%E6%8F%8F0016_%E5%89%AF%E6%9C%AC.jpg)|  ![](.\u002Fch3\u002F%E6%89%AB%E6%8F%8F0017_%E5%89%AF%E6%9C%AC.jpg)| \n|![](.\u002Fch3\u002F%E6%89%AB%E6%8F%8F0018_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch3\u002F%E6%89%AB%E6%8F%8F0019_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch3\u002F%E6%89%AB%E6%8F%8F0020_%E5%89%AF%E6%9C%AC.jpg)|  ![](.\u002Fch3\u002F%E6%89%AB%E6%8F%8F0021_%E5%89%AF%E6%9C%AC.jpg)| \n|![](.\u002Fch3\u002F%E6%89%AB%E6%8F%8F0022_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch3\u002F%E6%89%AB%E6%8F%8F0023_%E5%89%AF%E6%9C%AC.jpg)|--by 王博Kings| | \n\n\n## 第四章   决策树\n| 1 | 2 | 3 |4 |\n|:-----------:|:--------:|:---------:|:---------:|\n|![](.\u002Fch4\u002F%E6%89%AB%E6%8F%8F0024_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch4\u002F%E6%89%AB%E6%8F%8F0025_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch4\u002F%E6%89%AB%E6%8F%8F0026_%E5%89%AF%E6%9C%AC.jpg)|  ![](.\u002Fch4\u002F%E6%89%AB%E6%8F%8F0027_%E5%89%AF%E6%9C%AC.jpg)| \n|![](.\u002Fch4\u002F%E6%89%AB%E6%8F%8F0028_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch4\u002F%E6%89%AB%E6%8F%8F0029_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch4\u002F%E6%89%AB%E6%8F%8F0030_%E5%89%AF%E6%9C%AC.jpg)|  ![](.\u002Fch4\u002F%E6%89%AB%E6%8F%8F0031_%E5%89%AF%E6%9C%AC.jpg)| \n|![](.\u002Fch4\u002F%E6%89%AB%E6%8F%8F0032_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch4\u002F%E6%89%AB%E6%8F%8F0033_%E5%89%AF%E6%9C%AC.jpg)| ![](.\u002Fch4\u002F%E6%89%AB%E6%8F%8F0034_%E5%89%AF%E6%9C%AC.jpg)|  --by 王博Kings| \n\n## 第五章   神经网络\n| 1 | 2 | 3 |4 |\n|:-----------:|:--------:|:---------:|:---------:|\n|![image](.\u002Fch5\u002F%E6%89%AB%E6%8F%8F0035_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch5\u002F%E6%89%AB%E6%8F%8F0036_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch5\u002F%E6%89%AB%E6%8F%8F0037_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch5\u002F%E6%89%AB%E6%8F%8F0038_%E5%89%AF%E6%9C%AC.jpg)|\n![image](.\u002Fch5\u002F%E6%89%AB%E6%8F%8F0039_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch5\u002F%E6%89%AB%E6%8F%8F0040_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch5\u002F%E6%89%AB%E6%8F%8F0041_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch5\u002F%E6%89%AB%E6%8F%8F0042_%E5%89%AF%E6%9C%AC.jpg)|\n![image](.\u002Fch5\u002F%E6%89%AB%E6%8F%8F0043_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch5\u002F%E6%89%AB%E6%8F%8F0044_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch5\u002F%E6%89%AB%E6%8F%8F0045_%E5%89%AF%E6%9C%AC.jpg)|  --by 王博Kings| \n\n\n\n## 第六章   支持向量机\n| 1 | 2 | 3 |4 |\n|:-----------:|:--------:|:---------:|:---------:|\n|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0001_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0002_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0003_%E5%89%AF%E6%9C%AC.jpg)|\n![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0004_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0005_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0006_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0007_%E5%89%AF%E6%9C%AC.jpg)|\n![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0008_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0009_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0010_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0011_%E5%89%AF%E6%9C%AC.jpg)|\n![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0012_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0013_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0014_%E5%89%AF%E6%9C%AC.jpg)|![image](.\u002Fch6\u002F%E6%89%AB%E6%8F%8F0015_%E5%89%AF%E6%9C%AC.jpg)|\n\n## 第七章    贝叶斯分类器\n| 1 | 2 | 3 |4 |\n|:-----------:|:--------:|:---------:|:---------:|\n|![image](.\u002Fch7\u002F062.jpg)|![image](.\u002Fch7\u002F063.jpg)|![image](.\u002Fch7\u002F064.jpg)|![image](.\u002Fch7\u002F065.jpg)|\n|![image](.\u002Fch7\u002F066.jpg)|![image](.\u002Fch7\u002F067.jpg)|![image](.\u002Fch7\u002F068.jpg)|![image](.\u002Fch7\u002F069.jpg)\n|![image](.\u002Fch7\u002F070.jpg)|![image](.\u002Fch7\u002F071.jpg)|![image](.\u002Fch7\u002F072.jpg)|![image](.\u002Fch7\u002F073.jpg)\n|![image](.\u002Fch7\u002F074.jpg)|||--by 王博Kings| \n\n## 第八章   集成信息\n| 1 | 2 | 3 |4 |\n|:-----------:|:--------:|:---------:|:---------:|\n|![image](.\u002Fch8\u002F075.jpg)|![image](.\u002Fch8\u002F076.jpg)|![image](.\u002Fch8\u002F077.jpg)|![image](.\u002Fch8\u002F078.jpg)|\n|![image](.\u002Fch8\u002F079.jpg)|![image](.\u002Fch8\u002F080.jpg)|![image](.\u002Fch8\u002F081.jpg)|![image](.\u002Fch8\u002F082.jpg)|\n|![image](.\u002Fch8\u002F083.jpg)|![image](.\u002Fch8\u002F084.jpg)|![image](.\u002Fch8\u002F085.jpg)|![image](.\u002Fch8\u002F086.jpg)|\n\n## 第九章   聚类\n| 1 | 2 | 3 |4 |\n|:-----------:|:--------:|:---------:|:---------:|\n|![image](.\u002Fch9\u002F087.jpg)|![image](.\u002Fch9\u002F088.jpg)|![image](.\u002Fch9\u002F089.jpg)|![image](.\u002Fch9\u002F090.jpg)|\n|![image](.\u002Fch9\u002F091.jpg)|![image](.\u002Fch9\u002F092.jpg)|![image](.\u002Fch9\u002F093.jpg)|![image](.\u002Fch9\u002F094.jpg)|\n\n\n## 第十章  降维与度量学习\n| 1 | 2 | 3 |4 |\n|:-----------:|:--------:|:---------:|:---------:|\n|![image](.\u002Fch10\u002F095.jpg)|![image](.\u002Fch10\u002F096.jpg)|![image](.\u002Fch10\u002F097.jpg)|![image](.\u002Fch10\u002F098.jpg)|\n|![image](.\u002Fch10\u002F099.jpg)|![image](.\u002Fch10\u002F100.jpg)|![image](.\u002Fch10\u002F101.jpg)|![image](.\u002Fch10\u002F102.jpg)|\n|![image](.\u002Fch10\u002F103.jpg)|![image](.\u002Fch10\u002F104.jpg)||--by 王博Kings|\n","该项目是周志华《机器学习》一书的手写推导笔记，旨在帮助读者深入理解书中涉及的算法和理论。核心功能包括对书中各章节内容的详细手推公式及解释，覆盖了从模型评估与选择到强化学习等多个主题。技术特点在于其详尽的手写形式，适合于那些希望通过手动推导加深对机器学习算法理解的学习者使用，尤其是在学术研究或深度学习前的准备阶段。这份214页A4纸大小的笔记可以直接打印，方便随身携带学习。",2,"2026-06-11 03:24:54","top_topic"]