Fundamentals and Applications Related to Data Science, Machine Learning, and Statistical Processing
Author:
Affiliation:
1. College of Science and Engineering, Ritsumeikan Univ.
2. Data Science and AI Innovation Research Promotion Center, Shiga Univ.
Publisher
Society of Materials Science, Japan
Link
https://www.jstage.jst.go.jp/article/jsms/73/8/73_682/_pdf
Reference51 articles.
1. 1) https://tutorials.chainer.org/ja/tutorial.html (cited 2024-5-1).
2. 2) K. Fukushima, “Neocognitron: a self organizing neural network model for a mechanism of pattern recognition unaffected by shift in position”, Biological Cybernetics, Vol.36, No.4, pp.93-202 (1980).
3. 3) Y. LeCun, L. Bottou, Y. Bengio and P. Haffner, “Gradient-based learning applied to document recognition”, Proc. of IEEE, pp.2278-2324 (1998).
4. 4) K. Saito, “Zerokara tsukuru deep learning -python de manabu deep learning no riron to jisso-” (2016), O’Reilly Japan.
5. 5) Y. Azuma, “Neural network & backpropagation with python” (2018), SB Creative.
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