Handwritten digits recognition (0-9) Multi-class Logistic Regression 1. Vectorizing Logistic Regression (1) Vectorizing the cost function ...
源碼: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 ...
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Handwritten digits recognition (0-9) Multi-class Logistic Regression 1. Vectorizing Logistic Regression (1) Vectorizing the cost function ...
1. Feedforward and cost function; 2.Regularized cost function: 3.Sigmoid gradient The gradient for the sigmoid function can be computed ...
to compute the cost of linear regression[*] gradientDes ...
Question 1 Consider the problem of predicting how well a student does in her second year of college/university, given how well they did ...
線性回歸是機器學習中最基礎的算法,掌握了線性回歸算法,有利於以后更容易地理解其它復雜的算法。 線性回歸看似簡單,但是其中包含了線性代數,微積分,概率等諸多方面的知識。讓我們先從最簡單的形式開始。 一元線性回歸(Simple Linear Regression): 假設只有一個 ...
在之前的文章《機器學習---線性回歸(Machine Learning Linear Regression)》中說到,使用最小二乘回歸模型需要滿足一些假設條件。但是這些假設條件卻往往是人們容易忽略的地方。如果不考慮模型的適用情況,就只會得到錯誤的模型。下面來看一下,使用最小二乘回歸模型需要滿足 ...
前言 本文是多元線性回歸的練習,這里練習的是最簡單的二元線性回歸,參考斯坦福大學的教學網http://openclassroom.stanford.edu/MainFolder/DocumentPage.php?course=DeepLearning&doc ...
https://www.coursera.org/learn/machine-learning/exam/7pytE/linear-regression-with-multiple-variables 1。 Suppose m=4 students have taken some ...