solving the problem of overfitting:regularization 发生的在linear regression上面的overfitting问题 发生在logistic regression上面的overfitting 怎么解决overfitting regularization: cost function of linear regression parameters小的话,这样hypothesis就会变得简单,这样就不会overfitting 一般不会对θ0进…
The Problem of Overfitting Cost Function Regularized Linear Regression Note: [8:43 - It is said that X is non-invertible if m ≤ n. The correct statement should be that X is non-invertible if m < n, and may be non-invertible if m = n. We can apply reg…
https://jmetzen.github.io/2015-01-29/ml_advice.html Advice for applying Machine Learning This post is based on a tutorial given in a machine learning course at University of Bremen. It summarizes some recommendations on how to get started with machin…
https://www.quora.com/How-do-I-learn-mathematics-for-machine-learning   How do I learn mathematics for machine learning? Promoted by Time Doctor Software for productivity tracking. Time tracking and productivity improvement software with screenshots…
##Linear Regression with One Variable Linear regression predicts a real-valued output based on an input value. We discuss the application of linear regression to housing price prediction, present the notion of a cost function, and introduce the gradi…
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 Note Introduction Introduction What is Machine Learning? Two definitions of Machine Learning are offered. Arthur Samuel described it as:"the filed of study that gives computers the ability to learn without being explicitly programmed…
Bigger update: The content of this article is now available as a full-length video course that walks you through every step of the code. You can take the course for free (and access everything else on Lynda.com free for 30 days) if you sign up with t…
About this Course Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly i…
Chapter 1 Introduction 1.1 What Is Machine Learning? To solve a problem on a computer, we need an algorithm. An algorithm is a sequence of instructions that should be carried out to transform the input to output. For example, one can devise an algori…