CNN(卷積神經網絡)、RNN(循環神經網絡)、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

• 課程官網：CS231n: Convolutional Neural Networks for Visual Recognition
• Github：https://github.com/cs231n/cs231n.github.io | http://cs231n.github.io/
• 教學安排及大綱：Schedule and Syllabus
• 課程視頻：Youtube上查看Andrej Karpathy建立的播放列表，或者網易雲課堂
• 課程pdf及視頻下載：百度網盤下載，密碼是4efx

http://ufldl.stanford.edu/tutorial/supervised/ConvolutionalNeuralNetwork/
做者：zhwhong
連接：http://www.jianshu.com/p/182baeb82c71
來源：簡書
著做權歸做者全部。商業轉載請聯繫做者得到受權，非商業轉載請註明出處。

[斯坦福CS231n課程整理] Convolutional Neural Networks for Visual Recognition（附翻譯，做業）

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

斯坦福神經網絡視頻

https://www.youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv

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

深層學習爲什麼要「Deep」（上）
https://zhuanlan.zhihu.com/p/22888385
深層學習爲什麼要「Deep」（下）
https://zhuanlan.zhihu.com/p/24245040

熵與生命

https://yjango.gitbooks.io/superorganism/content/shang_yu_sheng_ming.html

《超智能體》做者講述深層神經網絡設計理念

https://v.douyu.com/show/j4xq3WDO3pRMLGNz

CNN(卷積神經網絡)、RNN(循環神經網絡)、DNN

https://www.zhihu.com/question/34681168

度強化學習（Deep Reinforcement Learning）入門：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

臺灣

http://www.jianshu.com/p/c30f7c944b66

爲何神經網絡牛逼？

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