# machine-learning-excercise-notebook-python

**Repository Path**: Ky1eYang/machine-learning-excercise-notebook-python

## Basic Information

- **Project Name**: machine-learning-excercise-notebook-python
- **Description**: Andrew Ng机器学习对应Python Jupyter Notebook
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-08-14
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 机器学习Jupyter Notebook

吴恩达的Machine Learning课程是非常适合机器学习的初学者。

但其assignment使用了Matlab/Octave语言，这显然已经不适合当前机器学习/深度学习技术的发展。

此Repository将其所有课程assignment内容更新为Python版本，并采用Jupyter Notebook的形式，方便阅读和实验。

## Jupyter Notebook (Python)

* [1.linear_regression](1.linear_regression)
* [2.logistic_regression](2.logistic_regression)
* [3.multi-class_classification_and_neural_network](3.multi-class_classification_and_neural_network)
* [4.nurual_network_back_propagation](4.nurual_network_back_propagation)
* [5.bias_vs_variance](5.bias_vs_variance)
* [6.svm](6.svm)
* [7.kmeans_and_PCA](7.kmeans_and_PCA)
* [8.anomaly_detection_and_recommendation](8.anomaly_detection_and_recommendation)

## 原始MATLAB版本
* [原始Assignment的MATLAB版本](original-machine-learning-MATLAB)

## 练习的描述PDF
* [原始Assignment的文字描述](Machine_Learning_Assignment(ex1-ex8).pdf)（整合为一个PDF）


如有疑问，请Submit issue或Pull Request，谢谢

## 更多

* [深度学习的Jupyter Notebooks](https://github.com/loveunk/deep-learning-exercise-notebook)
* [机器学习、深度学习的学习路径及知识总结](https://github.com/loveunk/machine-learning-deep-learning-notes)