Talk:人工神經網絡種類一覽
加主題最新留言：4 個月前由InternetArchiveBot喺主題對外連結有變 (2025年2月)度留言
對外連結有變 (2020年12月)
[編輯]各位編輯仝人：
我啱啱救返人工神經網絡種類一覽上面嘅 2 個對外連結。麻煩檢查下我改嘅嘢。有咩查詢，或者想隻機械人唔理啲外連，或者想隻機械人成版唔好掂，請睇呢版簡明嘅問答頁。我改咗呢啲外連：
- 由 http://wwwold.ece.utep.edu/research/webfuzzy/docs/kk-thesis/kk-thesis-html/node15.html 攞走咗失效連結標籤
- 加咗存檔 https://web.archive.org/web/20200730115600/https://towardsdatascience.com/generate-realistic-human-face-using-gan-e6136876e67c?gi=e517f59c9cbb 落 https://towardsdatascience.com/generate-realistic-human-face-using-gan-e6136876e67c
如果隻機械人有錯，請睇問答頁嘅指示。
唔該晒！—InternetArchiveBot (報告軟件缺陷) 2020年12月29號 (二) 04:14 (UTC)
對外連結有變 (2022年10月)
[編輯]各位編輯仝人：
我啱啱救返人工神經網絡種類一覽上面嘅 1 個對外連結。麻煩檢查下我改嘅嘢。有咩查詢，或者想隻機械人唔理啲外連，或者想隻機械人成版唔好掂，請睇呢版簡明嘅問答頁。我改咗呢啲外連：
- 加咗
{{dead link}}標籤落 https://codeburst.io/deep-learning-deep-belief-network-fundamentals-d0dcfd80d7d4 - 加咗存檔 https://web.archive.org/web/20200623142257/http://ailab.chonbuk.ac.kr/seminar_board/pds1_files/sparseAutoencoder.pdf 落 http://ailab.chonbuk.ac.kr/seminar_board/pds1_files/sparseAutoencoder.pdf
如果隻機械人有錯，請睇問答頁嘅指示。
唔該晒！—InternetArchiveBot (報告軟件缺陷) 2022年10月25號 (二) 07:35 (UTC)
對外連結有變 (2025年2月)
[編輯]各位編輯仝人：
我啱啱救返人工神經網絡種類一覽上面嘅 1 個對外連結。麻煩檢查下我改嘅嘢。有咩查詢，或者想隻機械人唔理啲外連，或者想隻機械人成版唔好掂，請睇呢版簡明嘅問答頁。我改咗呢啲外連：
- 加咗存檔 https://web.archive.org/web/20190401095745/https://towardsdatascience.com/understanding-bidirectional-rnn-in-pytorch-5bd25a5dd66 落 https://towardsdatascience.com/understanding-bidirectional-rnn-in-pytorch-5bd25a5dd66
如果隻機械人有錯，請睇問答頁嘅指示。
唔該晒！—InternetArchiveBot (報告軟件缺陷) 2025年2月12號 (三) 05:52 (UTC)
對外連結有變 (2025年2月)
[編輯]各位編輯仝人：
我啱啱救返人工神經網絡種類一覽上面嘅 9 個對外連結。麻煩檢查下我改嘅嘢。有咩查詢，或者想隻機械人唔理啲外連，或者想隻機械人成版唔好掂，請睇呢版簡明嘅問答頁。我改咗呢啲外連：
- 加咗存檔 https://web.archive.org/web/20210211033915/https://towardsdatascience.com/the-mostly-complete-chart-of-neural-networks-explained-3fb6f2367464?gi=6e2cd60cc3a5 落 https://towardsdatascience.com/the-mostly-complete-chart-of-neural-networks-explained-3fb6f2367464
- 加咗存檔 https://web.archive.org/web/20200612021817/https://towardsdatascience.com/hopfield-networks-are-useless-heres-why-you-should-learn-them-f0930ebeadcd?gi=222777bbb05 落 https://towardsdatascience.com/hopfield-networks-are-useless-heres-why-you-should-learn-them-f0930ebeadcd
- 加咗存檔 https://web.archive.org/web/20200701133728/https://towardsdatascience.com/restricted-boltzmann-machines-simplified-eab1e5878976?gi=ede9ae2a60e2 落 https://towardsdatascience.com/restricted-boltzmann-machines-simplified-eab1e5878976
- 加咗存檔 https://web.archive.org/web/20210211034054/https://towardsdatascience.com/introduction-to-extreme-learning-machines-c020020ff82b?gi=cb9d444ce79b 落 https://towardsdatascience.com/introduction-to-extreme-learning-machines-c020020ff82b
- 加咗存檔 https://web.archive.org/web/20230602023343/https://towardsdatascience.com/gentle-introduction-to-echo-state-networks-af99e5373c68 落 https://towardsdatascience.com/gentle-introduction-to-echo-state-networks-af99e5373c68
- 加咗存檔 https://web.archive.org/web/20210211033924/https://towardsdatascience.com/multi-layer-neural-networks-with-sigmoid-function-deep-learning-for-rookies-2-bf464f09eb7f?gi=9cedd57c66e3 落 https://towardsdatascience.com/multi-layer-neural-networks-with-sigmoid-function-deep-learning-for-rookies-2-bf464f09eb7f
- 加咗存檔 https://web.archive.org/web/20200804162618/https://towardsdatascience.com/radial-basis-functions-neural-networks-all-we-need-to-know-9a88cc053448?gi=35091307daef 落 https://towardsdatascience.com/radial-basis-functions-neural-networks-all-we-need-to-know-9a88cc053448
- 加咗存檔 https://web.archive.org/web/20200322095533/https://towardsdatascience.com/the-maths-behind-back-propagation-cf6714736abf 落 https://towardsdatascience.com/the-maths-behind-back-propagation-cf6714736abf
- 加咗存檔 https://web.archive.org/web/20200824075024/https://towardsdatascience.com/neural-networks-and-the-universal-approximation-theorem-8a389a33d30a?gi=1fc558436f 落 https://towardsdatascience.com/neural-networks-and-the-universal-approximation-theorem-8a389a33d30a
如果隻機械人有錯，請睇問答頁嘅指示。
唔該晒！—InternetArchiveBot (報告軟件缺陷) 2025年2月24號 (一) 05:28 (UTC)
對外連結有變 (2025年2月)
[編輯]各位編輯仝人：
我啱啱救返人工神經網絡種類一覽上面嘅 4 個對外連結。麻煩檢查下我改嘅嘢。有咩查詢，或者想隻機械人唔理啲外連，或者想隻機械人成版唔好掂，請睇呢版簡明嘅問答頁。我改咗呢啲外連：
- 加咗存檔 https://web.archive.org/web/20200908062051/https://towardsdatascience.com/understanding-variational-autoencoders-vaes-f70510919f73?gi=cd05519c4e15 落 https://towardsdatascience.com/understanding-variational-autoencoders-vaes-f70510919f73
- 加咗存檔 https://web.archive.org/web/20200804061545/https://towardsdatascience.com/denoising-autoencoders-explained-dbb82467fc2?gi=fc225b8faa 落 https://towardsdatascience.com/denoising-autoencoders-explained-dbb82467fc2
- 加咗存檔 https://web.archive.org/web/20210211034023/https://towardsdatascience.com/self-organizing-maps-for-dimension-reduction-data-visualization-and-clustering-ff966edd311c?gi=8c03143023d0 落 https://towardsdatascience.com/self-organizing-maps-for-dimension-reduction-data-visualization-and-clustering-ff966edd311c
- 加咗存檔 https://web.archive.org/web/20210211034024/https://towardsdatascience.com/understanding-compositional-pattern-producing-networks-810f6bef1b88?gi=89bf7ff64804 落 https://towardsdatascience.com/understanding-compositional-pattern-producing-networks-810f6bef1b88
如果隻機械人有錯，請睇問答頁嘅指示。