【文章推荐】CheeseZH: Stanford University: Machine Learning Ex5:Regularized Linear Regression and Bias v.s. Variance

原文：CheeseZH: Stanford University: Machine Learning Ex5:Regularized Linear Regression and Bias v.s. Variance

源码：https: github.com cheesezhe Coursera Machine Learning Exercise tree master ex Introduction： In this exercise, you will implement regularized linear regression and use it to study models with differ ...

2015-07-24 14:50 0 5713 推荐指数：

查看详情

CheeseZH: Stanford University: Machine Learning Ex3: Multiclass Logistic Regression and Neural Network Prediction

Handwritten digits recognition (0-9) Multi-class Logistic Regression 1. Vectorizing Logistic Regression (1) Vectorizing the cost function ...

CheeseZH: Stanford University: Machine Learning Ex4:Training Neural Network(Backpropagation Algorithm)

1. Feedforward and cost function; 2.Regularized cost function: 3.Sigmoid gradient The gradient for the sigmoid function can be computed ...

Coursera machine learning 第二周编程作业 Linear Regression

to compute the cost of linear regression[*] gradientDes ...

【Coursera - machine learning】 Linear regression with one variable-quiz

Question 1 Consider the problem of predicting how well a student does in her second year of college/university, given how well they did ...

机器学习---线性回归（Machine Learning Linear Regression）

线性回归是机器学习中最基础的算法，掌握了线性回归算法，有利于以后更容易地理解其它复杂的算法。线性回归看似简单，但是其中包含了线性代数，微积分，概率等诸多方面的知识。让我们先从最简单的形式开始。一元线性回归（Simple Linear Regression）：假设只有一个 ...

机器学习---最小二乘线性回归模型的5个基本假设（Machine Learning Least Squares Linear Regression Assumptions）

在之前的文章《机器学习---线性回归（Machine Learning Linear Regression）》中说到，使用最小二乘回归模型需要满足一些假设条件。但是这些假设条件却往往是人们容易忽略的地方。如果不考虑模型的适用情况，就只会得到错误的模型。下面来看一下，使用最小二乘回归模型需要满足 ...

Deep learning：二(linear regression练习)

　　前言　　本文是多元线性回归的练习，这里练习的是最简单的二元线性回归，参考斯坦福大学的教学网http://openclassroom.stanford.edu/MainFolder/DocumentPage.php?course=DeepLearning&doc ...

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 ...

原文：CheeseZH: Stanford University: Machine Learning Ex5:Regularized Linear Regression and Bias v.s. Variance

相关推荐

相关标签