https://www.quora.com/How-do-I-learn-machine-learning-1?redirected_qid=6578644   How Can I Learn X? Learning Machine Learning Learning About Computer Science Educational Resources Advice Artificial Intelligence How-to Question Learning New Things Lea…
Machine learning is a branch in computer science that studies the design of algorithms that can learn. Typical machine learning tasks are concept learning, function learning or “predictive modeling”, clustering and finding predictive patterns. These…
http://blog.csdn.net/pipisorry/article/details/44783647 机器学习Machine Learning - Andrew NG courses学习笔记 Anomaly Detection异常检測 Problem Motivation问题的动机 Anomaly detection example Applycation of anomaly detection Note:for Frauddetection: users behavior exam…
属性与特征: attribute: e.g., 'Mileage' feature: an attribute plus its value, e.g., 'Mileage = 15000' Note that some regression algorithm can be used for classification as well,and vice versa. For example,Logistic Regression is commonly used for classifica…
本节主要用于机器学习入门,介绍两个简单的分类模型: 决策树和随机森林 不涉及内部原理,仅仅介绍基础的调用方法 1. How Models Work 以简单的决策树为例 This step of capturing patterns from data is called fitting or training the model The data used to train the data is called the trainning data After the model has bee…
https://www.analyticsvidhya.com/blog/2015/07/difference-machine-learning-statistical-modeling/ http://normaldeviate.wordpress.com/2012/06/12/statistics-versus-machine-learning-5-2/ https://www.quora.com/What-is-the-difference-between-statistics-and-m…
Here is the note for lecture three. the linear model Linear model is a basic and important model in machine learning. 1. input representation     The data we get usually needs some changes, most of them is the input data.      In linear model,       …
A Gentle Introduction to the Gradient Boosting Algorithm for Machine Learning by Jason Brownlee on September 9, 2016 in XGBoost 0 0 0 0   Gradient boosting is one of the most powerful techniques for building predictive models. In this post you will d…
Introduction Optimization is always the ultimate goal whether you are dealing with a real life problem or building a software product. I, as a computer science student, always fiddled with optimizing my code to the extent that I could brag about its…
声明:本博客整理自博友@zhouyong计算广告与机器学习-技术共享平台,尊重原创,欢迎感兴趣的博友查看原文. 写在前面 记得在<Pattern Recognition And Machine Learning>一书中的开头有讲到:“概率论.决策论.信息论3个重要工具贯穿着<PRML>整本书,虽然看起来令人生畏…”.确实如此,其实这3大理论在机器学习的每一种技法中,或多或少都会出现其身影(不局限在概率模型). <PRML>书中原话:”This chapter also…