“第十六章 典型网络结构”版本间的差异
来自cslt Wiki
| 第10行： | 第10行： | ||
* AI100问：什么是循环神经网络？[http://aigraph.cslt.org/ai100/AI-100-107-什么是循环神经网络.pdf] | * AI100问：什么是循环神经网络？[http://aigraph.cslt.org/ai100/AI-100-107-什么是循环神经网络.pdf] | ||
* AI100问：什么是自编码器？[http://aigraph.cslt.org/ai100/AI-100-117-什么是自编码器.pdf] | * AI100问：什么是自编码器？[http://aigraph.cslt.org/ai100/AI-100-117-什么是自编码器.pdf] | ||
| + | |||
| 第31行： | 第32行： | ||
==高级读者== | ==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] | ||
* 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] | * 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, 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] | * 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) 04:20的版本
教学资料
扩展阅读
视频展示
演示链接
- Andrej Karpathy's CNN demo [8]
- Neural Net demo [9]
- Neural Net training demo [10]
- Quick draw, and let NN guess [11]
开发者资源
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" [15]
- 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 [16]
- 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. [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]
