第十七章 深度学习

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2022年8月5日 (五) 10:27Cslt讨论 | 贡献的版本

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教学资料

  • 教学参考
  • 课件
  • 小清爱提问:什么是深度学习(上)?[1]
  • 小清爱提问:什么是深度学习(下)?[2]

扩展阅读

视频展示

演示链接

  • ConvNetJS 深度神经网络演示 [3]
  • Leiden Demo for image classification [4]
  • CNN explainer[5]


  • Quick style transfer [6]
  • Pix2Pix[7]
  • AutoWriter[8]


开发者资源

  • Georgia Tech, Polo Club (可解释机器学习) [9]
  • Google developer courses [10]
  • ConvNetJS 代码 [11]

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" [12]
  • 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 [13]
  • 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. [14]
  • Elman, Jeffrey L. (1990). "Finding Structure in Time". Cognitive Science. 14 (2): 179–211. [15]
  • 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. [16]
  • 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). [17]
  • 王东,机器学习导论,第三章,神经模型,2021,清华大学出版社 [18]
  • Christopher M. Bishop, Neural Networks for Pattern Recognition [19]
  • Christopher M. Bishop, Pattern Recognition and Machine Learning [20]