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斯坦福机器学习笔记

Gitbook 地址: 戳我

本书为斯坦福吴恩达教授的在 coursera 上的机器学习公开课的知识笔记,涵盖了大部分课上涉及到的知识点和内容,因为篇幅有限,部分公式的推导没有记录在案,但推荐大家还是在草稿本上演算一遍,加深印象,知其然还要知其所以然。

本书涉及到的程序代码均放在了我个人的 github 上,采用了 python 实现,大部分代码都是相关学习算法的完整实现和测试。我没有放这门课程的 homework 代码,原因是 homework 布置的编程作业是填空式的作业,而完整实现一个算法虽然历经更多坎坷,但更有助于检验自己对算法理解和掌握程度。

本书的章节安排与课程对应关系为:

斯坦福课程 本书章节
Week 2 线性回归
Week 3 逻辑回归
Week 4-5 神经网络
Week 6 算法分析与优化
Week 7 SVM(支持向量机)
Week 8 K-Means、特征降维
Week 9 异常检测、推荐系统
Week 10 大规模机器学习
Week 11 案例--光学字符识别

学生我才疏学浅,对机器学习也只是刚刚入门,文中难免不少纰漏甚至严重错误,希望大家指正,这是对我最大的帮助。本书最大的目的也在于交流学习,而不在 star 和传播。任重而道远,你我共勉。

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mit-ml's Issues

多项式回归代码

您好,在多项式回归代码中,好像有问题,我试了您提供的源码和我自己的,都得不到书里的图像,好像是在numpy.power方法中,您将数据都求平方了

神经网络前馈计算的疑问

在神经网络代码中前馈函数fp(Thetas, X)中

有一项是a[l] = np.concatenate((np.ones((1, a[l].shape[1])), a[l])),注释是“添加偏置”

我对这一个操作有疑问,神经网络的每一层前馈不应该是WX + B吗?
应该有一个加操作,为什么这里没有体现?

biKmeans error in kmeans

        # 获得其他簇的样本
        ptsNoInCluster = dataSet[np.nonzero(
            clusterAssment[:, 0].A != j)[0]]
        # 获得剩余数据集的误差
        nonSplitedError = np.sum(ptsNoInCluster[:, 1])

获得剩余数据集的误差不需要dataSet,而是clusterAssment
即整体改为:
# 获得剩余数据集的误差
nonSplitedError = np.sum(clusterAssment[np.nonzero(
clusterAssment[:, 0].A != j)[0]][:, 1])

数学公式问题

你好,首先非常感谢您的笔记,感觉获益匪浅,特别是书中与python代码的结合

不过我自己有个问题,就是我在用gitbook编辑数学公式的时候,显示的是这样的

如下:
image
可是当我publish成功后去阅读的时候,公式又变成了这样子:

image
我非常苦难,请问您知道如何解决这问题吗
对了,我用的是gitbook的网页版的

linear_regression.py文件报错,运行环境2.7/3.6均失败

Traceback (most recent call last):
File "/home/kkk/code/mit-ml-master/linear_regression/test_sgd.py", line 11, in
X, y = regression.loadDataSet('data/ex1.txt');
File "/home/kkk/code/mit-ml-master/linear_regression/regression.py", line 39, in loadDataSet
y.append(float(curLine[-1]))
ValueError: invalid literal for float(): 6.1101 17.592

斯坦福机器学习笔记

你好。请问可以提供笔记的pdf版本吗?我想下载下来观看,但是gitbook上没有pdf版本。

Gitbook的笔记无法访问

你好,想问下关于gitbook的笔记为什么打不开呀?github上的笔记链接直接跳转到了gitbook的官网……注册了gitbook之后仍然无法正常打开你在github中放的gitbook链接……

求数据集~

请问你的数据集是从哪儿下的呀,能不能放上来一下

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