DIY Deep Learning for Vision:A Full-Day Caffe Tutorial

Caffe (Convolution Architecture For Feature Extraction)作为深度学习CNN一个非常火的框架,对于初学者来说,搭建Linux下的Caffe平台是学习深度学习关键的一步,其过程也比较繁琐,回想起当初折腾的那几天,遂总结一下Ubuntu14.04的配置过程,方便以后新手能在此少走弯路. 1. 安装build-essentials 安装开发所需要的一些基本包 sudo apt-get install build-essential 2. 安装NVID

转自:http://www.jeremydjacksonphd.com/category/deep-learning/ Deep Learning Resources Posted on May 13, 2015 Videos Deep Learning and Neural Networks with Kevin Duh: course page NY Course by Yann LeCun: 2014 version, 2015 version NIPS 2015 Deep Learnin

Machine and Deep Learning with Python Education Tutorials and courses Supervised learning superstitions cheat sheet Introduction to Deep Learning with Python How to implement a neural network How to build and run your first deep learning network Neur

My deep learning reading list 主要是顺着Bengio的PAMI review的文章找出来的.包括几本综述文章,将近100篇论文,各位山头们的Presentation.全部都可以在google上找到.BTW:由于我对视觉尤其是检测识别比较感兴趣,所以关于DL的应用主要都是跟Vision相关的.在其他方面比如语音或者NLP,很少或者几乎没有.个人非常看好CNN和Sparse Autoencoder,这个list也反映了我的偏好,仅供参考. Review Book Lis

DEEP LEARNING WITH STRUCTURE Charlie Tang is a PhD student in the Machine Learning group at the University of Toronto, working with Geoffrey Hinton and Ruslan Salakhutdinov, whose research interests include machine learning, computer vision and cogni

Deep Learning References ________________________________________________________________ Review Book List:[2009 Thesis] Learning Deep Generative Models.pdf[2009] Learning Deep Architectures for AI.pdf[2013 DengLi Review] Deep Learning for Signal and

本文中,我会根据下大家image classification常用的cnn模型,针对cifar10(for 物体识别),mnist(for 字符识别)& ImageNet(for 物体识别)做一个model 总结. 本文不讲coding(coding请见Convolution Neural Network (CNN) 原理与实现篇) 本文不涉及公司内部资料,纯公开资料汇总 好,本文就从数据集说起,对数据集不熟悉的小伙伴请先去了解下这3个数据集,下面我们针对每个数据集画出其通用模型. ＝＝＝＝＝＝

几个不错的深度学习教程,基本都有视频和演讲稿.附两篇综述文章和一副漫画.还有一些以后补充. Jeff Dean 2013 @ Stanford http://i.stanford.edu/infoseminar/dean.pdf 一个对DL能干什么的入门级介绍,主要涉及Google在语音识别.图像处理和自然语言处理三个方向上的一些应用.参<Spanner and Deep Learning>(2013-01-19) Hinton 2009 A tutorial on Deep Learning

Deep Learning Methods for Vision CVPR 2012 Tutorial  9:00am-5:30pm, Sunday June 17th, Ballroom D (Full day) Rob Fergus (NYU), Honglak Lee (Michigan), Marc'Aurelio Ranzato (Google) Ruslan Salakhutdinov(Toronto), Graham Taylor(Guelph), Kai Yu(Baidu)  O