Machine Learning 第三周

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Machine Learning 第三周

ML week3 逻辑回归 Logistic Function h_\theta(x)=g(\theta^Tx) g(t)=\frac{1}{1+e^{-z}} 当t大于0, 即下面公式成立时,y=1 \frac{1}{1+e^{-{\theta^Tx}}}>0.5 => {\theta^Tx}>0 关于theta与数据 y(x)=\theta_0+\theta_1x1+\theta_2x2 y(x)=\theta_0+\theta_1x_1+\theta_2x_2+\theta_3 x…

Hand on Machine Learning第三章课后作业(1)：垃圾邮件分类

import os import email import email.policy 1. 读取邮件数据 SPAM_PATH = os.path.join( "E:\\3.Study\\机器学习\\Hand on Machine Learning\\第三章:分类\\spam_data") spam_path = os.path.join(SPAM_PATH, "spam") ham_path = os.path.join(SPAM_PATH, "easy_…

Machine Learning - 第6周（Advice for Applying Machine Learning、Machine Learning System Design）

In Week 6, you will be learning about systematically improving your learning algorithm. The videos for this week will teach you how to tell when a learning algorithm is doing poorly, and describe the 'best practices' for how to 'debug' your learning…

Machine Learning - 第3周（Logistic Regression、Regularization）

Logistic regression is a method for classifying data into discrete outcomes. For example, we might use logistic regression to classify an email as spam or not spam. In this module, we introduce the notion of classification, the cost function for logi…

Machine Learning第十一周笔记：photo OCR

博客已经迁移至Marcovaldo's blog (http://marcovaldong.github.io/) 刚刚完毕了Cousera上Machine Learning的最后一周课程.这周介绍了machine learning的一个应用:photo OCR(optimal character recognition,光学字符识别),以下将笔记整理在以下. Photo OCR Problem Description and Pipeline 最后几小节介绍机器学习的一个应用--photo O…

Machine Learning – 第2周（Linear Regression with Multiple Variables、Octave/Matlab Tutorial）

Machine Learning – Coursera Octave for Microsoft Windows GNU Octave官网 GNU Octave帮助文档 (有900页的pdf版本) Octave 4.0.0 安装 win7(文库) Octave学习笔记(文库) octave入门(文库) WIN7 64位系统安装JDK并配置环境变量(总是显示没有安装Java) MathWorks This week we're covering linear regression with mul…