“第十七章 深度学习”版本间的差异

来自cslt Wiki
跳转至： 导航、 搜索
第1行： 第1行：
  
 +
==教学资料==
 +
*[[教学参考-17|教学参考]]
 +
*[http://aigraph.cslt.org/courses/17/course-17.pptx 课件]
 +
*小清爱提问：什么是深度学习（上）？[https://mp.weixin.qq.com/s?__biz=Mzk0NjIzMzI2MQ==&mid=2247487252&idx=1&sn=b3dac3e2afbe2b7ebff901ba358ee3e0&chksm=c30805d6f47f8cc02d8a284fb416c7767f815861f3656a605378bbf6caf718f11191637b81de&scene=178#rd
 +
]
 +
*小清爱提问：什么是深度学习（下）？[https://mp.weixin.qq.com/s?__biz=Mzk0NjIzMzI2MQ==&mid=2247487260&idx=1&sn=c6ee1b8e09fcec9d9dfc96ddd06d874f&chksm=c30805def47f8cc8498b5c77c0ad720b45f02e78126fe9ed06e0a4465d3a970874b229692f29&scene=178#rd
 +
]
  
−
* ConvNetJS 深度神经网络演示 [https://cs.stanford.edu/people/karpathy/convnetjs/]
+
==扩展阅读==
  
−
* ConvNetJS 代码 [https://github.com/karpathy/convnetjs]
 
  
−
* Leiden  Demo for image classification [http://destiny.liacs.nl/]
 
  
−
* CNN explainer[https://poloclub.github.io/cnn-explainer/]
+
==视频展示==
  
 +
==演示链接==
 +
* ConvNetJS 深度神经网络演示 [https://cs.stanford.edu/people/karpathy/convnetjs/]
 +
* ConvNetJS 代码 [https://github.com/karpathy/convnetjs]
 +
* Leiden  Demo for image classification [http://destiny.liacs.nl/]
 +
* CNN explainer[https://poloclub.github.io/cnn-explainer/]
 
* 可解释机器学习 [https://poloclub.github.io/]
 
* 可解释机器学习 [https://poloclub.github.io/]
−
 
−
===Demo===
 
  
 
* Quick style transfer [https://tenso.rs/demos/fast-neural-style/]
 
* Quick style transfer [https://tenso.rs/demos/fast-neural-style/]
第17行： 第25行：
 
* AutoWriter[https://cyborg.tenso.rs/]
 
* AutoWriter[https://cyborg.tenso.rs/]
  
−
===开发者资源===
+
 
 +
==开发者资源==
  
 
*Google developer courses [https://developers.google.com/machine-learning/crash-course?hl=zh-cn]
 
*Google developer courses [https://developers.google.com/machine-learning/crash-course?hl=zh-cn]
 +
 +
==高级读者==
 +
 +
* Fukushima, Kunihiko (1980). "Neocognitron: A Self-organizing Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position" [https://www.cs.princeton.edu/courses/archive/spr08/cos598B/Readings/Fukushima1980.pdf]
 +
* Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, L. D. Jackel, Backpropagation Applied to Handwritten Zip Code Recognition; AT&T Bell Laboratories [http://yann.lecun.com/exdb/publis/pdf/lecun-89e.pdf]
 +
* Hopfield, J. J. (1982). "Neural networks and physical systems with emergent collective computational abilities". Proceedings of the National Academy of Sciences. 79 (8): 2554–2558. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC346238]
 +
* Elman, Jeffrey L. (1990). "Finding Structure in Time". Cognitive Science. 14 (2): 179–211. [https://doi.org/10.1016%2F0364-0213%2890%2990002-E]
 +
* Jordan, Michael I. (1997-01-01). "Serial Order: A Parallel Distributed Processing Approach". Neural-Network Models of Cognition - Biobehavioral Foundations. Advances in Psychology. Neural-Network Models of Cognition. Vol. 121. pp. 471–495.  [https://doi.org/10.1016%2Fs0166-4115%2897%2980111-2]
 +
* Hinton, G. E., & Zemel, R. S. (1994). Autoencoders, minimum description length and Helmholtz free energy. In Advances in neural information processing systems 6 (pp. 3-10). [https://proceedings.neurips.cc/paper/1993/file/9e3cfc48eccf81a0d57663e129aef3cb-Paper.pdf]
 +
* 王东，机器学习导论,第三章，神经模型，2021,清华大学出版社 [http://mlbook.cslt.org]
 +
* Christopher M. Bishop, Neural Networks for Pattern Recognition [https://www.amazon.com/Networks-Recognition-Advanced-Econometrics-Paperback/dp/0198538642]
 +
* Christopher M. Bishop, Pattern Recognition and Machine Learning [https://www.amazon.com/-/es/Christopher-M-Bishop/dp/0387310738/ref=d_pd_sbs_sccl_3_3/143-3751675-4420139?pd_rd_w=2LB2s&content-id=amzn1.sym.3676f086-9496-4fd7-8490-77cf7f43f846&pf_rd_p=3676f086-9496-4fd7-8490-77cf7f43f846&pf_rd_r=XM3AJDN6MSM89CR1ZFV7&pd_rd_wg=QjVJC&pd_rd_r=10293f3a-8b44-4f6d-b6ee-9595387e2f18&pd_rd_i=0387310738&psc=1]

2022年8月5日 (五) 10:24的版本

教学资料

]

]

扩展阅读

视频展示

演示链接

  • ConvNetJS 深度神经网络演示 [1]
  • ConvNetJS 代码 [2]
  • Leiden Demo for image classification [3]
  • CNN explainer[4]
  • 可解释机器学习 [5]
  • Quick style transfer [6]
  • Pix2Pix[7]
  • AutoWriter[8]


开发者资源

  • Google developer courses [9]

高级读者

  • Fukushima, Kunihiko (1980). "Neocognitron: A Self-organizing Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position" [10]
  • Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, L. D. Jackel, Backpropagation Applied to Handwritten Zip Code Recognition; AT&T Bell Laboratories [11]
  • Hopfield, J. J. (1982). "Neural networks and physical systems with emergent collective computational abilities". Proceedings of the National Academy of Sciences. 79 (8): 2554–2558. [12]
  • Elman, Jeffrey L. (1990). "Finding Structure in Time". Cognitive Science. 14 (2): 179–211. [13]
  • Jordan, Michael I. (1997-01-01). "Serial Order: A Parallel Distributed Processing Approach". Neural-Network Models of Cognition - Biobehavioral Foundations. Advances in Psychology. Neural-Network Models of Cognition. Vol. 121. pp. 471–495. [14]
  • Hinton, G. E., & Zemel, R. S. (1994). Autoencoders, minimum description length and Helmholtz free energy. In Advances in neural information processing systems 6 (pp. 3-10). [15]
  • 王东，机器学习导论,第三章，神经模型，2021,清华大学出版社 [16]
  • Christopher M. Bishop, Neural Networks for Pattern Recognition [17]
  • Christopher M. Bishop, Pattern Recognition and Machine Learning [18]
取自“http://index.cslt.org/mediawiki/index.php?title=第十七章_深度学习&oldid=38892”