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coursera-machine-learning's Introduction

项目简介

本项目是 吴恩达机器学习 课程的 笔记 和 作业。课程作业原先使用的是 Octave 和 MATLAB。不过笔者觉得无论是对 Machine Learning 的学习还是对未来工程项目的开发 Python 都更为合适。所以笔者就使用 Python 将课程作业重新实现了一遍。 希望这个项目能帮助大家理清课程的内容,理解算法背后的模型,掌握一些 Python 基本库的使用。

Python 依赖包

pip install numpy
pip install matplotlib
pip install scipy

第一周 | 线性回归

  • 笔记
  • 作业说明
  • 数据:ex1data1.txtex1data2.txt
  • 作业文件:ex1.pyex1_multi.py
python ex1.py 
python ex1_multi.py 

第二周 | 逻辑回归

  • 笔记
  • 作业说明
  • 数据:ex2data2.txtex2data2.txt
  • 作业文件:ex2.pyex2_reg.py
python ex2.py 
python ex2_reg.py 

第三周 | 神经网络 | 多分类问题

  • 笔记
  • 作业说明
  • 数据:ex3data1.matex3weights.mat
  • 作业文件:ex3.pyex3_nn.py
python ex3.py 
python ex3_nn.py 

第四周 | 神经网络 | 反向传播算法

python ex4.py

第五周 | 方差与偏差

python ex5.py

第六周 | 支持向量机

python ex6.py
python ex6_spam.py

第七周 | 无监督学习算法 | k-means 与 PCA

  • 笔记
  • 作业说明
  • 数据:bird_small.pngex7data1.matex7data2.matex7faces.mat
  • 作业文件:ex7.pyex7_pca.py
python ex7.py
python ex7_pca.py

第八周 | 异常检测与协同过滤

  • 笔记
  • 作业说明
  • 数据:ex8data1.matex8data2.matex8_movies.matex8_movieParams.matmovie_ids.txt
  • 作业文件:ex8.pyex8_cofi.py
python ex8.py
python ex8_cofi.py

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