Ha, it's English time, let's spend a few minutes to learn a simple machine learning example in a simple passage. Introduction What is machine learning? you design methods for machine to learn itself and improve itself. By leading into the machine lea…
Machine Learning Methods: Decision trees and forests This post contains our crib notes on the basics of decision trees and forests. We first discuss the construction of individual trees, and then introduce random and boosted forests. We also discuss…
In my last article, I stated that for practitioners (as opposed to theorists), the real prerequisite for machine learning is data analysis, not math. One of the main reasons for making this statement, is that data scientists spend an inordinate amoun…
##机器学习(Machine Learning)&深度学习(Deep Learning)资料(Chapter 2)---#####注:机器学习资料[篇目一](https://github.com/ty4z2008/Qix/blob/master/dl.md)共500条,[篇目二](https://github.com/ty4z2008/Qix/blob/master/dl2.md)开始更新------#####希望转载的朋友**一定要保留原文链接**,因为这个项目还在继续也在不定期更新.希望看到…
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…
Recommended Books Here is a list of books which I have read and feel it is worth recommending to friends who are interested in computer science. Machine Learning Pattern Recognition and Machine Learning Christopher M. Bishop A new treatment of classi…
Problems[show] Classification Clustering Regression Anomaly detection Association rules Reinforcement learning Structured prediction Feature engineering Feature learning Online learning Semi-supervised learning Unsupervised learning Learning to rank…
Why The Golden Age Of Machine Learning is Just Beginning Even though the buzz around neural networks, artificial intelligence, and machine learning has been relatively recent, as many know, there is nothing new about any of these methods. If so many…
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…
目录 1. \(l_0\)范数和\(l_1\)范数 2. \(l_2\)范数 3. 核范数(nuclear norm) 参考文献 使用正则化有两大目标: 抑制过拟合: 将先验知识融入学习过程,比如稀疏.低秩.平滑等特性. 结合第二点以及贝叶斯估计的观点,正则化项(regularizer)就是先验概率项. 监督学习中绝大多数任务都可以概括为以下最小化目标: \[ w^* = \arg\min_w {\sum_i {L(y_i; f(x_i;w))} + \lambda \Omega(w)} \]…