锅炉matlab程序代码-Stanford-ML-Python:完成AndrewNg在Coursera上的ML课程中的练习。为了学习，所有练习
锅matlab程序代码Andrew
Ng
的机器学习编程练习：Pythonized
斯坦福大学机器学习课程由
Andrew
Ng
在
Coursera
上讲授
我自己在
Python
中实现了课程练习，因此我选择在线托管。
锅炉板代码改写也改写了。
不使用原始
Octave/Matlab
文件的几个原因：
到目前为止，Python
比
Oct/Mat
更有用和广泛使用。
目的是获得更多使用
python
数据库的经验。
原始的课程作业为学生做了大量的跑腿工作。
在我看来，仅仅填补所讲的空白不足以彻底理解材料。
解释结果的责任更大。
在原始作业提供预期值和对结果的解释的情况下，重新实现自然会导致不同的结果，需要在理解结果和潜在改进（更贴近生活）方面进行更多思考。
当然，推导也相当缺乏。
想在可能的情况下包括其他派生，但优先级较低。
文件格式一般旨在模仿课程练习的格式。
确切的变化因部分而异；
这些在相关文件夹中有详细说明。
没有提出实际意见；
重新实现提交代码似乎没有很好地利用时间。
因此，虽然我不能保证与答案完全相同，但可能的答案与原始作业中给出的答案相匹配。
通过绘图或类似方式进行的
文件下载
资源详情
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