转载自http://baojie.org/blog/2013/01/27/deep-learning-tutorials/
Stanford Deep Learning wiki: http://deeplearning.stanford.edu/wiki/index.php/Main_Page
几个不错的深度学习教程,基本都有视频和演讲稿。附两篇综述文章和一副漫画。还有一些以后补充。
Jeff Dean 2013 @ Stanford
http://i.stanford.edu/infoseminar/dean.pdf
一个对DL能干什么的入门级介绍,主要涉及Google在语音识别、图像处理和自然语言处理三个方向上的一些应用。参《Spanner and Deep Learning》(2013-01-19)
Hinton 2009
A tutorial on Deep Learning
Slides http://videolectures.net/site/normal_dl/tag=52790/jul09_hinton_deeplearn.pdf
Video http://videolectures.net/jul09_hinton_deeplearn/ (3 hours)
从神经网络的背景来分析DL,为什么要有DL说得很清楚。对DL的基本模型结构也说得很清楚。十分推荐
更多Hinton的教程 http://www.cs.toronto.edu/~hinton/nntut.html
斯坦福的Deep Learning公开课(2012)
Samy Bengio, Tom Dean and Andrew Ng
http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=DeepLearning
教学语言是Matlab。
参2011年的课程CS294A/CS294W Deep Learning and Unsupervised Feature Learning
更多的斯坦福工作: Deep Learning in Natural Language Processing
NIPS 2009 tutorial
这个介绍了DL在三个方向上的应用:tagging (parsing), semantic search, concept labeling
Ronan Collobert的Senna是一个c的深度学习实现,只有2000多行代码
ACL 2012 tutorial
Deep Learning for NLP (without Magic)
Video: http://www.youtube.com/watch?v=IF5tGEgRCTQ&list=PL4617D0E28A5781B0
Kai Yu’s Tutorial
Slides link: http://pan.baidu.com/share/link?shareid=136269&uk=2267174042[1]
Video link: KaiYu_report.mp4 (519.2 MB)
Theano Deep Learning Tutorial
这个是实战, 如何用Python实现深度学习
http://deeplearning.net/tutorial/
Survey Papers
很多,不过初学看这两篇应该就够了
Yoshua Bengio, Aaron Courville, Pascal Vincent. (2012) Representation Learning: A Review and New Perspectives
Yoshua Bengio (2009). Learning Deep Architectures for AI.
更多
- Itamar Arel, Derek C. Rose, and Thomas P. Karnowski. (2010) Deep Machine Learning – A New Frontier in Artificial Intelligence Research 这篇没什么公式,也不长,就是笼统的介绍一下
- 截至2009的一些重要文章 http://www.iro.umontreal.ca/~lisa/twiki/bin/view.cgi/Public/ReadingOnDeepNetworks
最后来个漫画
Deep Learning虽好,也要牢记它的局限
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