scruel
7 years ago
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| @@ -8,12 +8,22 @@ https://www.coursera.org/learn/machine-learning | |||
| 本项目包含课程中的所有课后作业以及笔记，目前正在将手写笔记进行电子化。 | |||
| 本项目包含课程中的课后作业以及笔记： | |||
| 1. 笔记(notes)都为中文，为了便于复习和扩充等，尽量会按照视频目录，以及视频内容进行提炼整理。 | |||
| 2. 遵循[荣誉准则][honor code]，现已移除已通过的课后编程作业的源代码，之后会改为指导笔记形式陆续更新。 | |||
| 电子版笔记基于手写笔记，时间有限再加上为了追求清晰精确，更新较慢请大佬们谅解😭。 | |||
| 码的很辛苦，大佬们如果觉得笔记整理的还不错，记得保持关注，也欢迎分享哦。 | |||
| 感谢支持(\*^_^\*)。 | |||
| For Andrew Ng's machine learning course on Coursera. | |||
| Including assignments and notes, notes are WIP. | |||
| @@ -73,8 +83,8 @@ By: Scruel | |||
| [zhihu]: https://zhuanlan.zhihu.com/p/32781741 | |||
| [baidupan]: https://pan.baidu.com/s/1mkmnRIC | |||
| [bilibili_zh]: http://www.bilibili.com/video/av9912938?bbid=F8173D95-FF96-47EF-B7F4-0779D698B8051978infoc | |||
| [bilibili_en1]: https://www.bilibili.com/video/av17624209/?from=search&seid=15848135050308500663 | |||
| [bilibili_en2]: https://www.bilibili.com/video/av17624412/?from=search&seid=15848135050308500663 | |||
| [bilibili_en1]: https://www.bilibili.com/video/av17624209/?from=search&seid=15848135050308500663 | |||
| [bilibili_en2]: https://www.bilibili.com/video/av17624412/?from=search&seid=15848135050308500663 | |||
| [GitHub with MathJax]: https://chrome.google.com/webstore/detail/ioemnmodlmafdkllaclgeombjnmnbima | |||
| [Typora]: https://typora.io/ | |||
| [honor code]: https://www.coursera.org/learn/machine-learning/supplement/nh65Z/machine-learning-honor-code | |||
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| @@ -220,7 +220,7 @@ header, .context-menu, .megamenu-content, footer { font-family: "Segoe UI", Aria | |||
| </style> | |||
| </head> | |||
| <body class='typora-export' > | |||
| <div id='write' class = 'is-node show-fences-line-number'><h1><a name='header-n136' class='md-header-anchor '></a>吴恩达(Andrew Ng)机器学习公开课中文笔记</h1><p><a href='https://github.com/scruel/ML-AndrewNg-Notes/'>GitHub 项目首页</a></p><p> </p><p><a href='./week1.html'>week1</a></p><ol start='' ><li>引言(Introduction)</li><li>单变量线性回归(Linear Regression with One Variable)</li></ol><p><a href='./week2.html'>week2</a></p><ol start='3' ><li>线性代数回顾(Linear Algebra Review)</li><li>多变量线性回归(Linear Regression with Multiple Variables)</li><li>Octave/Matlab 指南(Octave/Matlab Tutorial)</li></ol><p><a href='./week3.html'>week3</a></p><ol start='6' ><li>逻辑回归(Logistic Regression)</li><li>正则化(Regularization)</li></ol><p><a href='./week4.html'>week4</a></p><ol start='8' ><li>神经网络：表达(Neural Networks: Representation)</li></ol><p><a href='./week5.html'>week5</a></p><ol start='9' ><li>神经网络：学习(Neural Networks: Learning)</li></ol><p><a href='./week6.html'>week6</a></p><ol start='10' ><li>机器学习应用的建议(Advice for Applying Machine Learning)</li><li>机器学习系统设计(Machine Learning System Design)</li></ol><p><a href='./week7.html'>week7</a></p><ol start='12' ><li>支持向量机(Support Vector Machines)</li></ol><p><a href='./week8.html'>week8</a></p><ol start='13' ><li>无监督学习(Unsupervised Learning)</li><li>降维(Dimensionality Reduction)</li></ol><p><a href='./week9.html'>week9</a></p><ol start='15' ><li>异常检测(Anomaly Detection)</li><li>推荐系统(Recommender Systems)</li></ol><p><a href='./week10.html'>week10</a></p><ol start='17' ><li>大规模机器学习(Large Scale Machine Learning)</li></ol><p><a href='./week11.html'>week11</a></p><ol start='18' ><li>实战：图像光学识别(Application Example: Photo OCR)</li></ol><p> </p><p> </p><p><a href='http://creativecommons.org/licenses/by-nc/4.0/' target='_blank'><img src='https://i.creativecommons.org/l/by-nc/4.0/88x31.png' alt='Creative Commons License' /></a></p><p>This work is licensed under a <a href='http://creativecommons.org/licenses/by-nc/4.0/' target='_blank'>Creative Commons Attribution-NonCommercial 4.0 International License</a>.</p><p> </p><p><a href='https://zhuanlan.zhihu.com/p/32781741'>知乎文章</a></p><p>By: Scruel</p><p> </p><p><div style="display:none"> | |||
| <div id='write' class = 'is-node show-fences-line-number'><h1><a name='header-n135' class='md-header-anchor '></a>吴恩达(Andrew Ng)机器学习公开课中文笔记</h1><p>电子版笔记基于手写笔记，时间有限再加上为了追求清晰精确，更新较慢请大佬们谅解😭。</p><p>码的很辛苦，大佬们如果觉得笔记整理的还不错，记得保持关注，也欢迎分享哦。</p><p>感谢支持(*^_^*)。</p><p><a href='https://github.com/scruel/ML-AndrewNg-Notes/'>GitHub 项目首页</a> | <a href='https://zhuanlan.zhihu.com/p/32781741'>知乎文章</a></p><p> </p><p><a href='./week1.html'>week1</a></p><ol start='' ><li>引言(Introduction)</li><li>单变量线性回归(Linear Regression with One Variable)</li></ol><p><a href='./week2.html'>week2</a></p><ol start='3' ><li>线性代数回顾(Linear Algebra Review)</li><li>多变量线性回归(Linear Regression with Multiple Variables)</li><li>Octave/Matlab 指南(Octave/Matlab Tutorial)</li></ol><p><a href='./week3.html'>week3</a></p><ol start='6' ><li>逻辑回归(Logistic Regression)</li><li>正则化(Regularization)</li></ol><p><a href='./week4.html'>week4</a></p><ol start='8' ><li>神经网络：表达(Neural Networks: Representation)</li></ol><p><a href='./week5.html'>week5</a></p><ol start='9' ><li>神经网络：学习(Neural Networks: Learning)</li></ol><p><a href='./week6.html'>week6</a></p><ol start='10' ><li>机器学习应用的建议(Advice for Applying Machine Learning)</li><li>机器学习系统设计(Machine Learning System Design)</li></ol><p><a href='./week7.html'>week7</a></p><ol start='12' ><li>支持向量机(Support Vector Machines)</li></ol><p><a href='./week8.html'>week8</a></p><ol start='13' ><li>无监督学习(Unsupervised Learning)</li><li>降维(Dimensionality Reduction)</li></ol><p><a href='./week9.html'>week9</a></p><ol start='15' ><li>异常检测(Anomaly Detection)</li><li>推荐系统(Recommender Systems)</li></ol><p><a href='./week10.html'>week10</a></p><ol start='17' ><li>大规模机器学习(Large Scale Machine Learning)</li></ol><p><a href='./week11.html'>week11</a></p><ol start='18' ><li>实战：图像光学识别(Application Example: Photo OCR)</li></ol><p> </p><p> </p><h2><a name='header-n238' class='md-header-anchor '></a>License</h2><p><a href='http://creativecommons.org/licenses/by-nc/4.0/' target='_blank'><img src='https://i.creativecommons.org/l/by-nc/4.0/88x31.png' alt='Creative Commons License' /></a></p><p>This work is licensed under a <a href='http://creativecommons.org/licenses/by-nc/4.0/' target='_blank'>Creative Commons Attribution-NonCommercial 4.0 International License</a>.</p><p> </p><p>By: Scruel</p><p> </p><p><div style="display:none"> | |||
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