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
- GitHub Repo:Halfrost-Field
- Follow: halfrost . GitHub
- Source: github.com/halfrost/Ha
来源: https://juejin.im/post/5ab98efb518825558b3df021