目录 前言 第一周:Welcome 1.1 What is Machine Learning? 1.2 Linear Regression with One Variable 第二周:Linear Regression with Multiple Variables 2.1 Multivariate Linear Regression 2.2 Computing Parameters Analytically 2.3 Octave/Matlab Tutorial 第三周:Logistic Regression 3.1 Logistic Regression 3.2 Regularization 第四周:Neural Networks: Representation 4.1 Neural Networks Representation 第五周:Neural Networks: Learning 5.1 Neural Networks Learning 5.2 Backpropagation in Practice 第六周:Advice for Applying Machine Learning 6.1 Advice for Applying Machine Learning 6.2 Machine Learning System Design 第七周:Support Vector Machines 7.1 Support Vector Machines 第八周:Unsupervised Learning 8.1 Unsupervised Learning 8.2 Dimensionality Reduction 第九周:Anomaly Detection 9.1 Anomaly Detection 9.2 Recommender Systems 第十周:Large Scale Machine Learning 10.1 Large Scale Machine Learning 第十一周:Application Example: Photo OCR 11.1 Application Example: Photo OCR 附录 GitHub Repo:Halfrost-Field Follow: halfrost · GitHub Source: https://github.com/halfrost/Halfrost-Field/blob/master/contents/Machine_Learning/contents.md