# index

# 吴恩达(Andrew Ng)机器学习公开课中文笔记

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week1

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

week2

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

week3

6. 逻辑回归(Logistic Regression)
7. 正则化(Regularization)

week4

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

week5

9. 神经网络：学习(Neural Networks: Learning)

week6

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

week7

12. 支持向量机(Support Vector Machines)

week8

13. 无监督学习(Unsupervised Learning)
14. 降维(Dimensionality Reduction)

week9

15. 异常检测(Anomaly Detection)
16. 推荐系统(Recommender Systems)

week10

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

week11

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

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