diff --git a/README.md b/README.md index 49a0c02..8baf406 100644 --- a/README.md +++ b/README.md @@ -13,22 +13,9 @@ https://www.coursera.org/learn/machine-learning 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。 +感谢关注，欢迎分享。 - - -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. - -You can read it by Typora or any other similar markdown editor. +[知乎文章][zhihu] ## Read @@ -42,8 +29,6 @@ You can read it by Typora or any other similar markdown editor. 4. 笔记源码(.md)基于支持 LaTeX 的 markdown 编辑器 [Typora][Typora]，其他类似的编辑器也可以阅读及编辑，注意其他编辑器可能会产生排版问题。 - - ## Resources 方便网络不方便的同学学习 @@ -72,13 +57,17 @@ You can read it by Typora or any other similar markdown editor. This work is licensed under a [Creative Commons Attribution-NonCommercial 4.0 International License][CC BY-NC 4.0]. +Copyright © Scruel. All Rights Reserved. +**注：转载请注明出处，禁止用于任何商业用途（包括广告形式）** -Copyright © Scruel. All Rights Reserved. +## Donate + +觉得不错，不如请我喝杯咖啡： +![image](image/20181115103549.png) -[知乎文章][zhihu] [zhihu]: https://zhuanlan.zhihu.com/p/32781741 [baidupan]: https://pan.baidu.com/s/1mkmnRIC diff --git a/image/20181115103549.png b/image/20181115103549.png new file mode 100644 index 0000000..f981f4f Binary files /dev/null and b/image/20181115103549.png differ diff --git a/index.html b/index.html index a702d50..a7ecf7c 100644 --- a/index.html +++ b/index.html @@ -2,12 +2,15 @@ -index.md - -

吴恩达(Andrew Ng)机器学习公开课中文笔记

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(*^_^*)。

有打赏需求的大佬们，支付宝账号即为 GitHub 主页邮箱--，嗯……应该没有吧。

GitHub 项目首页 | 知乎文章

 

week1

  1. 引言(Introduction)
  2. 单变量线性回归(Linear Regression with One Variable)

week2

  1. 线性代数回顾(Linear Algebra Review)
  2. 多变量线性回归(Linear Regression with Multiple Variables)
  3. Octave/Matlab 指南(Octave/Matlab Tutorial)

week3

  1. 逻辑回归(Logistic Regression)
  2. 正则化(Regularization)

week4

  1. 神经网络：表达(Neural Networks: Representation)

week5

  1. 神经网络：学习(Neural Networks: Learning)

week6

  1. 机器学习应用的建议(Advice for Applying Machine Learning)
  2. 机器学习系统设计(Machine Learning System Design)

week7

  1. 支持向量机(Support Vector Machines)

week8

  1. 无监督学习(Unsupervised Learning)
  2. 降维(Dimensionality Reduction)

week9

  1. 异常检测(Anomaly Detection)
  2. 推荐系统(Recommender Systems)

week10

  1. 大规模机器学习(Large Scale Machine Learning)

week11

  1. 实战：图像光学识别(Application Example: Photo OCR)

 

 

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

 

By: Scruel

 

+ +

吴恩达(Andrew Ng)机器学习公开课中文笔记

感谢关注，欢迎分享。

GitHub 项目首页 | 知乎文章

 

week1

  1. 引言(Introduction)
  2. 单变量线性回归(Linear Regression with One Variable)

week2

  1. 线性代数回顾(Linear Algebra Review)
  2. 多变量线性回归(Linear Regression with Multiple Variables)
  3. Octave/Matlab 指南(Octave/Matlab Tutorial)

week3

  1. 逻辑回归(Logistic Regression)
  2. 正则化(Regularization)

week4

  1. 神经网络：表达(Neural Networks: Representation)

week5

  1. 神经网络：学习(Neural Networks: Learning)

week6

  1. 机器学习应用的建议(Advice for Applying Machine Learning)
  2. 机器学习系统设计(Machine Learning System Design)

week7

  1. 支持向量机(Support Vector Machines)

week8

  1. 无监督学习(Unsupervised Learning)
  2. 降维(Dimensionality Reduction)

week9

  1. 异常检测(Anomaly Detection)
  2. 推荐系统(Recommender Systems)

week10

  1. 大规模机器学习(Large Scale Machine Learning)

week11

  1. 实战：图像光学识别(Application Example: Photo OCR)

 

 

License

[Creative Commons License][CC BY-NC 4.0]

This work is licensed under a [Creative Commons Attribution-NonCommercial 4.0 International License][CC BY-NC 4.0].

Copyright © Scruel. All Rights Reserved.

注：转载请注明出处，禁止用于任何商业用途（包括广告形式）

Donate

觉得不错，不如请我喝杯咖啡： +image