【[Machine Learning (Andrew NG courses)]IV.Linear Regression with Multiple Variables】的更多相关文章

[Machine Learning (Andrew NG courses)]IV.Linear Regression with Multiple Variables

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[Machine Learning (Andrew NG courses)]II. Linear Regression with One Variable

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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…

Coursera machine learning 第二周 quiz 答案 Linear Regression with Multiple Variables

https://www.coursera.org/learn/machine-learning/exam/7pytE/linear-regression-with-multiple-variables 1. Suppose m=4 students have taken some class, and the class had a midterm exam and a final exam. You have collected a dataset of their scores on the…

Machine Learning - Andrew Ng - Coursera

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【原】Coursera—Andrew Ng机器学习—Week 2 习题—Linear Regression with Multiple Variables 多变量线性回归

Gradient Descent for Multiple Variables [1]多变量线性模型  代价函数 Answer:AB [2]Feature Scaling 特征缩放 Answer:D [3]学习速率 α Answer: B,因为第一个比第二个下降的快.第三个上升说明α太大 [4]Mean Normalization Answer:C [5]Normal Equation Answer:D Linear Regression with Multiple Variables [1]…

机器学习 (二) 多变量线性回归 Linear Regression with Multiple Variables

文章内容均来自斯坦福大学的Andrew Ng教授讲解的Machine Learning课程,本文是针对该课程的个人学习笔记,如有疏漏,请以原课程所讲述内容为准.感谢博主Rachel Zhang 的个人笔记,为我做个人学习笔记提供了很好的参考和榜样. § 2. 多变量线性回归 Linear Regression with Multiple Variables 1 多特征值(多变量) Multiple Features(Variables) 首先,举例说明了多特征值(多变量)的情况.在下图的例子中,…

Linear regression with multiple variables(多特征的线型回归)算法实例_梯度下降解法(Gradient DesentMulti)以及正规方程解法(Normal Equation)

,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,, 1 % Exercise 1: Linear regression with multiple variables %% Initialization %% ================ Part 1: Featu…

机器学习（三）--------多变量线性回归(Linear Regression with Multiple Variables)

机器学习(三)--------多变量线性回归(Linear Regression with Multiple Variables) 同样是预测房价问题  如果有多个特征值 那么这种情况下  假设h表示为  公式可以简化为 两个矩阵相乘   其实就是所有参数和变量相乘再相加  所以矩阵的乘法才会是那样 那么他的代价函数就是 同样是寻找使J最小的一系列参数 python代码为 比如这种     那么X是[1,2,3]   y也是[1,2,3]   那么令theta0 = 0  theta1 = 1 …

（原创）Stanford Machine Learning (by Andrew NG) --- (week 1) Linear Regression

Andrew NG的Machine learning课程地址为:https://www.coursera.org/course/ml 在Linear Regression部分出现了一些新的名词,这些名词在后续课程中会频繁出现: Cost Function Linear Regression Gradient Descent Normal Equation Feature Scaling Mean normalization 损失函数 线性回归 梯度下降 正规方程 特征归一化 均值标准化 Mode…