“第十七章 深度学习”版本间的差异

2022年8月5日 (五) 10:24的版本

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]
• ConvNetJS 代码 [4]
• Leiden Demo for image classification [5]
• CNN explainer[6]
• 可解释机器学习 [7]

• Quick style transfer [8]
• Pix2Pix[9]
• AutoWriter[10]

开发者资源

• Google developer courses [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]