sierkinhane / cs229-ml-implementation

Implementation of algorithms introduced in CS229.

[2019-11-23] Update: Add Conditional Generative Adversarial Nets on MNIST in 01-UnsupervisedLerning

[2019-11-7] Update: Add Generative Adversarial Nets on MNIST in 01-UnsupervisedLerning

[2019-11-5] Update: Add 99.76% accuracy mnist model

CS229-ML-Implements(CS229机器学习算法的Python实现)

Implements of cs229(Machine Learning taught by Andrew Ng) in python.

CS229 Machine Learning Xmind:

CS229 Machine Learning course and notes:

OpenCourse

cs229-Notes

Syllabus：

• Linear Regression

• Normal Equation

• Locally Weighted Regression

• Logistic Regression

• Perceptron Algorithm

• Newton Method

• Softmax Regression

• Gaussian Discriminant Analysis

• Naive Bayes spam-filter

Examples

Linear Regression

Locally Weighted Regression

Logistic Regression

Softmax Regression

Gaussian Discriminant Analysis

Naive Bayes spam-filter

TO BE CONTINUED