This repository contains Matlab/Octave implementations of certain exercises from the course Machine Learning by Andrew Ng on Coursera, Summer 2017. Some code annotations were written in Chinese.
这个仓库包含了 Andrew Ng 2017 年夏于 Coursera 平台上开设的课程 Machine Learning 相关资料,包括 Matlab/Octave 实践。代码注释和笔记资料使用中文。
- Linear Regression
- One variable
- Multiple variable
- Gradient descent
- Normal equation
- Project: House pricing Prediction
- Logistic Regression
- Sigmoid function
- Polynomial Regression
- Visualization
- Datasets
- Decision boundaries
- Algorithm analysis
- Model representation (e.g. Hidden layers in Neural Networks)
- Algorithm Analysis
- Vectorization
- Learning curve
- Training/cross-validation/testing curve
- Regularization
- Regularized Linear Regression
- Regularized Logistic Regression
- Regularized Neural Networks
- Regularized Normal Equation
- Multi-class Classification
- One-vs-all classification
- Project: One-vs-all Prediction
- Neural Networks
- Feedforward
- Backpropagation
- Project: Handwritten Digits Recognition
- Support Vector Machine
- Gaussian Kernels
- Project: Email Spam Classification (also a bit of NLP)
- Clustering
- K-means Clustering
- PCA(Principal Component Analysis)
- Dimensionality Reduction
- Project: Image Compression
- Project: Face Feature Extraction
- Anomaly Detection
- Gaussian Distribution
- Recommender System
- Collaborative filtering
- Project: Movie rating