http://cs231n.github.io/neural-networks-1
https://arxiv.org/pdf/1603.07285.pdf
https://adeshpande3.github.io/adeshpande3.github.io/A-Beginner's-Guide-To-Understanding-Convolutional-Neural-Networks/
Applied Deep Learning - Part 1: Artificial Neural Networks
- 课程官网：CS231n: Convolutional Neural Networks for Visual Recognition
- Github：https://github.com/cs231n/cs231n.github.io | http://cs231n.github.io/
- 教学安排及大纲：Schedule and Syllabus
- 课程视频：Youtube上查看Andrej Karpathy创建的播放列表，或者网易云课堂
- 课程pdf及视频下载：百度网盘下载，密码是4efx
http://ufldl.stanford.edu/tutorial/supervised/ConvolutionalNeuralNetwork/
作者：zhwhong
链接：http://www.jianshu.com/p/182baeb82c71
來源：简书
著作权归作者所有。商业转载请联系作者获得授权，非商业转载请注明出处。
[斯坦福CS231n课程整理] Convolutional Neural Networks for Visual Recognition（附翻译，作业）
http://www.jianshu.com/p/182baeb82c71
CS231n Winter 2016 Lecture 1 Introduction and Historical Context-F ...
https://www.youtube.com/watch?v=2uiulzZxmGg
http://cs231n.stanford.edu/syllabus.html
http://cs231n.stanford.edu/2016/syllabus
https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/
- karpathy/neuraltalk2: Efficient Image Captioning code in Torch, Examples
- Shaoqing Ren, et al, “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks”, 2015, arXiv:1506.01497
- Neural Network Architectures, Eugenio Culurciello’s blog
- CS231n Convolutional Neural Networks for Visual Recognition, Stanford
- Clarifai / Technology
- Machine Learning is Fun! Part 3: Deep Learning and Convolutional Neural Networks
- Feature extraction using convolution, Stanford
- Wikipedia article on Kernel (image processing)
- Deep Learning Methods for Vision, CVPR 2012 Tutorial
- Neural Networks by Rob Fergus, Machine Learning Summer School 2015
- What do the fully connected layers do in CNNs?
- Convolutional Neural Networks, Andrew Gibiansky
- A. W. Harley, “An Interactive Node-Link Visualization of Convolutional Neural Networks,” in ISVC, pages 867-877, 2015 (link). Demo
- Understanding Convolutional Neural Networks for NLP
- Backpropagation in Convolutional Neural Networks
- A Beginner’s Guide To Understanding Convolutional Neural Networks
- Vincent Dumoulin, et al, “A guide to convolution arithmetic for deep learning”, 2015, arXiv:1603.07285
- What is the difference between deep learning and usual machine learning?
- How is a convolutional neural network able to learn invariant features?
- A Taxonomy of Deep Convolutional Neural Nets for Computer Vision
- Honglak Lee, et al, “Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations” (link)
https://cambridgespark.com/content/tutorials/convolutional-neural-networks-with-keras/index.html
http://www.wildml.com/2015/11/understanding-convolutional-neural-networks-for-nlp/
http://deeplearning.net/tutorial/lenet.html
http://cs231n.github.io/convolutional-networks/
http://ufldl.stanford.edu/tutorial/supervised/ConvolutionalNeuralNetwork/
https://cambridgespark.com/content/tutorials/convolutional-neural-networks-with-keras/index.html
http://colah.github.io/posts/2014-03-NN-Manifolds-Topology/
http://googleresearch.blogspot.com/2015/06/inceptionism-going-deeper-into-neural.html
http://cs.stanford.edu/people/karpathy/convnetjs//demo/classify2d.html
斯坦福神经网络视频
https://www.youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv
http://cs231n.github.io/convolutional-networks/
深层学习为何要“Deep”（上）
https://zhuanlan.zhihu.com/p/22888385
深层学习为何要“Deep”（下）
https://zhuanlan.zhihu.com/p/24245040
熵与生命
https://yjango.gitbooks.io/superorganism/content/shang_yu_sheng_ming.html
《超智能体》作者讲述深层神经网络设计理念
https://v.douyu.com/show/j4xq3WDO3pRMLGNz
CNN(卷积神经网络)、RNN(循环神经网络)、DNN
https://www.zhihu.com/question/34681168
度强化学习（Deep Reinforcement Learning）入门：RL base & DQN-DDPG-A3C introduction
https://zhuanlan.zhihu.com/p/25239682
http://colah.github.io/posts/2015-08-Understanding-LSTMs/
https://zhuanlan.zhihu.com/p/22888385
https://www.zhihu.com/question/22553761
https://mp.weixin.qq.com/s?__biz=MzA3MzI4MjgzMw==&mid=402032673&idx=1&sn=d7e636b6d033cbcf8a74dfaf710e9ccf#rd
http://wiki.jikexueyuan.com/project/deep-learning/recognition-digit.html
http://cs231n.github.io/convolutional-networks/
https://github.com/rasbt/python-machine-learning-book/tree/master/faq
*
http://www.jianshu.com/p/c30f7c944b66
为什么神经网络牛逼？
https://www.zhihu.com/question/41667903/answer/130691120
https://ujjwalkarn.me/2016/08/09/quick-intro-neural-networks/
http://home.agh.edu.pl/~vlsi/AI/backp_t_en/backprop.html
https://github.com/rasbt/python-machine-learning-book/tree/master/faq
https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/
http://karpathy.github.io/2015/05/21/rnn-effectiveness/
https://medium.com/@ageitgey/machine-learning-is-fun-80ea3ec3c471
http://cs231n.github.io/convolutional-networks/
http://www.jianshu.com/p/1afda7000d8e
http://ufldl.stanford.edu/tutorial/supervised/MultiLayerNeuralNetworks/
http://www.wildml.com/2015/11/understanding-convolutional-neural-networks-for-nlp/
http://deeplearning.net/tutorial/lenet.html
http://ufldl.stanford.edu/tutorial/supervised/ConvolutionalNeuralNetwork/
http://blog.163.com/lipse_huang/blog/static/19165754520133954138888/
https://en.wikipedia.org/wiki/Convolutional_neural_network
http://www.wildml.com/2015/11/understanding-convolutional-neural-networks-for-nlp/
https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/
http://cs231n.github.io/convolutional-networks/
http://cs231n.github.io/classification/
http://cs231n.github.io/linear-classify/
http://ufldl.stanford.edu/tutorial/supervised/MultiLayerNeuralNetworks/
https://medium.com/@ageitgey/machine-learning-is-fun-part-2-a26a10b68df3
Hacker's guide to Neural Networks
http://karpathy.github.io/neuralnets/