Deep Learning资源整理

教程:
http://neuralnetworksanddeeplearning.com – Python-netowrk, network2, network3，从浅层神经网络到深度学习

http://deeplearning.stanford.edu/wiki/index.PHP/UFLDL_Tutorial –Andrew ng

http://cs231n.github.io/convolutional-networks/ –Fe-iFei Li

http://colah.github.io/ — colah

http://hangtwenty.github.io/dive-into-machine-learning/ –

http://www.thetalkingmachines.com/

http://vision.princeton.edu/courses/COS598/2015sp/ *

http://vision.stanford.edu/teaching/cs231n/slides/ *

http://bjsc.github.io/SuperLR-Page/

http://bjsc.github.io/SuperLR-Page/pages/ 66天写的逻辑回归

https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/

http://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html 概率图模型

书籍:
http://www.deeplearningbook.org/

视频:

http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=DeepLearning

http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=MachineLearning

http://videolectures.net/jul09_hinton_deeplearn/

https://classroom.udacity.com/courses/ud730/lessons/6370362152/concepts/63798118150923

论文:

http://deeplearning.net/

http://arxiv.org/

caffe相关

http://ethereon.github.io/netscope/quickstart.html

http://caffe.berkeleyvision.org/

博客:

http://colah.github.io/

http://www.jianshu.com/p/9dc9f41f0b29

2d-convolution: https://grzegorzgwardys.wordpress.com/2016/04/22/8/#unique-identifier

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1.the first time I heard the term (hidden layer) I thought it must have some deep philosophical or mathematical significance - but it really means nothing more than “not an input or an output”.