CNN(卷积神经网络)、RNN(循环神经网络)、DNN，LSTM

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

https://medium.com/towards-data-science/applied-deep-learning-part-1-artificial-neural-networks-d7834f67a4f6

• 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

http://cs231n.stanford.edu/

http://colah.github.io/

https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/

1. karpathy/neuraltalk2: Efficient Image Captioning code in Torch, Examples
2. Shaoqing Ren, et al, “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks”, 2015, arXiv:1506.01497
3. Neural Network Architectures, Eugenio Culurciello’s blog
4. CS231n Convolutional Neural Networks for Visual Recognition, Stanford
5. Clarifai / Technology
6. Machine Learning is Fun! Part 3: Deep Learning and Convolutional Neural Networks
7. Feature extraction using convolution, Stanford
8. Wikipedia article on Kernel (image processing)
9. Deep Learning Methods for Vision, CVPR 2012 Tutorial
10. Neural Networks by Rob Fergus, Machine Learning Summer School 2015
11. What do the fully connected layers do in CNNs?
12. Convolutional Neural Networks, Andrew Gibiansky
13. A. W. Harley, “An Interactive Node-Link Visualization of Convolutional Neural Networks,” in ISVC, pages 867-877, 2015 (link). Demo
14. Understanding Convolutional Neural Networks for NLP
15. Backpropagation in Convolutional Neural Networks
16. A Beginner’s Guide To Understanding Convolutional Neural Networks
17. Vincent Dumoulin, et al, “A guide to convolution arithmetic for deep learning”, 2015, arXiv:1603.07285
18. What is the difference between deep learning and usual machine learning?
19. How is a convolutional neural network able to learn invariant features?
20. A Taxonomy of Deep Convolutional Neural Nets for Computer Vision
21. 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://online.cambridgecoding.com/notebooks/eWReNYcAfB/implementing-logistic-regression-classifier-trained-by-gradient-descent-4

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

https://adeshpande3.github.io/adeshpande3.github.io/A-Beginner%27s-Guide-To-Understanding-Convolutional-Neural-Networks/

http://cs231n.github.io/convolutional-networks/

https://github.com/rasbt/python-machine-learning-book/tree/master/faq

台湾

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://www.analyticsvidhya.com/blog/2017/06/architecture-of-convolutional-neural-networks-simplified-demystified/

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/

https://adeshpande3.github.io/adeshpande3.github.io/A-Beginner%27s-Guide-To-Understanding-Convolutional-Neural-Networks/

http://ufldl.stanford.edu/tutorial/supervised/MultiLayerNeuralNetworks/

https://medium.com/@ageitgey/machine-learning-is-fun-part-3-deep-learning-and-convolutional-neural-networks-f40359318721

https://medium.com/@ageitgey/machine-learning-is-fun-part-2-a26a10b68df3

Hacker's guide to Neural Networks

http://karpathy.github.io/neuralnets/

Deformable-ConvNets

https://www.zhihu.com/question/57493889

https://github.com/msracver/Deformable-ConvNets