吴恩达(Andrew Ng)机器学习公开课中文笔记

该笔记系转载Scruel，如有侵权请联系删除，在此感谢作者。

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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)