diff --git a/README.md b/README.md index c7cf2e1..4bfc40f 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ [![github](https://img.shields.io/github/stars/scruel/ML-AndrewNg-Notes?logo=github&label=Stars)](https://github.com/scruel/ML-AndrewNg-Notes) [![star](https://img.shields.io/badge/dynamic/json?label=Stars&query=%24.stargazers_count&url=https%3A%2F%2Fgitee.com%2Fapi%2Fv5%2Frepos%2Fscruel%2FML-AndrewNg-Notes&logo=gitee)](https://gitee.com/scruel/ML-AndrewNg-Notes) -💌 Sponsor the project: https://afdian.net/@scruel +💌 Sponsor this project: https://afdian.net/@scruel diff --git a/html/index.html b/html/index.html index 42bf301..b05a7f2 100644 --- a/html/index.html +++ b/html/index.html @@ -228,7 +228,7 @@ header, .context-menu, .megamenu-content, footer { font-family: "Segoe UI", Aria

吴恩达(Andrew Ng)机器学习公开课中文笔记

github -star

💌 Sponsor the project: https://afdian.net/@scruel

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.

Copyright © Scruel. All Rights Reserved.

 

本人所作的所有笔记内容禁止任何商业形式（包括广告形式）的转载，非商业形式的转载请先联系我授权，在承诺不会用于商业用途后方可使用，且需声明转载地址（GitHub）。

 

+star

💌 Sponsor this project: https://afdian.net/@scruel

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.

Copyright © Scruel. All Rights Reserved.

 

本人所作的所有笔记内容禁止任何商业形式（包括广告形式）的转载，非商业形式的转载请先联系我授权，在承诺不会用于商业用途后方可使用，且需声明转载地址（GitHub）。