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CS229-ML-Implementation

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Implementation of algorithms introduced in CS229.

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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

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Pythondeeplearningmachine-learning-algorithms

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PublishedAug 1, 2026
UpdatedSep 17, 2026
Category编程语言
PricingOpen source

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