查看“深度学习-入门导读”的源代码

=入门导读=

深度学习教程。

==斯坦福==
Andrew Ng实验室
[http://deeplearning.stanford.edu/tutorial/ DL11]
[http://ufldl.stanford.edu/tutorial/ DL22]

# Stanford Deep Learning tutorials [http://ufldl.stanford.edu/wiki/index.php/UFLDL_Tutorial DL_tutorials]

==谷歌==
Jeff Dean谷歌大脑

# Jeff Dean, Large-Scale Deep Learning for Intelligent Computer Systems, WSDM 2016. [http://research.google.com/pubs/jeff.html WSDM_keynote]
# Jeffrey Dean et al. "Large scale distributed deep networks." Advances in Neural Information Processing Systems. 2012.
# TensorFlow: A System for Large-Scale Machine Learning, OSDI 2016. [https://www.usenix.org/system/files/conference/osdi16/osdi16-abadi.pdf TensorFlow_OSDI2016_paper] [http://research.google.com/pubs/pub45381.html TensorFlow_paper]

==Nature/Science==
# DAVID E. RUMELHART, GEOFFREY E. HINTON & RONALD J. WILLIAMS, Learning representations by back-propagating errors, Nature 323, 533 - 536,09 October 1986. [http://www.nature.com/nature/journal/v323/n6088/abs/323533a0.html SGD]
# LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton. "Deep learning." Nature 521(7553), pp:436-444, 2015. [http://www.nature.com/nature/journal/v521/n7553/full/nature14539.html Deep_Learning_Nature]

==书籍==
# Yoshua Bengio, Ian Goodfellow, Aaron Courville, Deep Learning, MIT Press, 2016. [http://www.deeplearningbook.org/ DeepLearningBook]