Computational Methods in Bayesian Analysis Computational Methods in Bayesian Analysis [Markov chain Monte Carlo][Gibbs Sampling][The Metropolis-Hastings Algorithm][Random-walk Metropolis-Hastings][Adaptive Metropolis] About the author This noteboo…
Are you a interested in taking a course with us? Learn about our programs or contact us at hello@zipfianacademy.com. There are plenty of articles and discussions on the web about what data science is, what qualitiesdefine a data scientist, how to nur…
链接. General Books on Electromagnetics When our department recently reviewed our junior-level text, we were struck by the large number of books now available from wh ich to teach introductory electromagnetics. Here, I mention only my two personal favo…
Common sense reduced to computation - Pierre-Simon, marquis de Laplace (1749–1827) Inventor of Bayesian inference 贝叶斯方法的逻辑十分接近人脑的思维:人脑的优势不是计算,在纯数值计算方面,可以说几十年前的计算器就已经超过人脑了. 人脑的核心能力在于推理,而记忆在推理中扮演了重要的角色,我们都是基于已知的常识来做出推理.贝叶斯推断也是如此,先验就是常识,在我们有了新的观测数据后,就可以…
Statistical approaches to randomised controlled trial analysis The statistical approach used in the design and analysis of the vast majority of clinical studies is often referred to as classical or frequentist. Conclusions are made on the results of…
Contribution: 1) Systematic interpretation to existing face sketch synthesis methods. 2) Bayesian face sketch synthesis: apply the spatial neighboring constraint to both the neighbor selection model and the wieght computation model. Problem: s代表targe…
[it-ebooks]电子书列表 [2014]: Learning Objective-C by Developing iPhone Games || Leverage Xcode and Objective-C to develop iPhone games http://it-ebooks.info/book/3544/Learning Web App Development || Build Quickly with Proven JavaScript Techniques http:…
最近在学深度学习相关的东西,在网上搜集到了一些不错的资料,现在汇总一下: Free Online Books by Yoshua Bengio, Ian Goodfellow and Aaron Courville Neural Networks and Deep Learning42 by Michael Nielsen Deep Learning27 by Microsoft Research Deep Learning Tutorial23 by LISA lab, University…
转自:机器学习(Machine Learning)&深度学习(Deep Learning)资料 <Brief History of Machine Learning> 介绍:这是一篇介绍机器学习历史的文章,介绍很全面,从感知机.神经网络.决策树.SVM.Adaboost到随机森林.Deep Learning. <Deep Learning in Neural Networks: An Overview> 介绍:这是瑞士人工智能实验室Jurgen Schmidhuber写的最…