文件名称：主成分回归代码matlab及例子-CS229_Python:Ng的机器学习课程Python解决方案
文件大小：27.84MB
文件格式：ZIP
更新时间：2024-06-15 06:42:06
系统开源
主成分回归代码matlab及示例Coursera机器学习 该存储库包含Andrew Ng课程中某些练习的python实现。 对于课程中的许多作业，系统会指导您创建某些算法的完整，独立的Octave / MATLAB实现（例如，线性回归和逻辑回归）。 其余的作业取决于课程作者提供的其他代码。 对于该存储库中的大多数代码，我改用了Scikit-learn之类的现有Python实现。 进行中的工作。 参考：
【文件预览】：
CS229_Python-master
----README.md(3KB)
----pdf()
--------Programming Exercise 7 - K-means Clustering and Principal Component Analysis.pdf(178KB)
--------Programming Exercise 5 - Regularized Linear Regression and Bias v.s. Variance.pdf(138KB)
--------Programming Exercise 3 - Multi-class Classification and Neural Networks.pdf(142KB)
--------Programming Exercise 6 - Support Vector Machines.pdf(158KB)
--------Programming Exercise 1 - Linear Regression.pdf(247KB)
--------Programming Exercise 8 - Anomaly Detection and Recommender Systems.pdf(125KB)
--------Programming Exercise 4 - Neural Networks Learning.pdf(136KB)
--------Programming Exercise 2 - Logistic Regression.pdf(241KB)
----LICENSE.md(1KB)
----notebooks()
--------Programming Exercise 7 - K-means Clustering and Principal Component Analysis.ipynb(171KB)
--------Programming Exercise 2 - Logistic Regression.ipynb(145KB)
--------Programming Exercise 4 - Neural Networks Learning.ipynb(8KB)
--------Programming Exercise 1 - Linear Regression.ipynb(267KB)
--------.ipynb_checkpoints()
--------Programming Exercise 3 - Multi-class Classification and Neural Networks.ipynb(23KB)
--------Programming Exercise 5 - Regularized Linear Regression and Bias v.s. Variance.ipynb(118KB)
--------Programming Exercise 8 - Anomaly Detection and Recommender Systems.ipynb(109KB)
--------Programming Exercise 6 - Support Vector Machines.ipynb(177KB)
--------data()