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Analyzing the Results - Advances in Condition Monitoring, Pt VII

tvhahn.com · published 31 May 2021

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https://colab.research.google.com/github/tvhahn/Manufacturing-Data-Science-with-Python/blob/master/Metal%20Machining/1.C_anomaly-results.ipynb
colab.research.google.com
http://dm.snu.ac.kr/static/docs/TR/SNUDM-TR-2015-03.pdf
dm.snu.ac.kr
https://jamesmccaffrey.wordpress.com/2021/03/11/anomaly-detection-using-variational-autoencoder-reconstruction-probability/
jamesmccaffrey.wordpress.com
http://adamlineberry.ai/vae-series/vae-code-experiments
adamlineberry.ai
https://en.wikipedia.org/wiki/Receiver_operating_characteristic
en.wikipedia.org
https://en.wikipedia.org/wiki/Precision_and_recall
en.wikipedia.org
https://stats.stackexchange.com/a/372977https://stats.stackexchange.com/a/372977
stats.stackexchange.com
https://en.wikipedia.org/wiki/Ensemble_learning
en.wikipedia.org
https://github.com/tvhahn/ml-tool-wear
github.com
https://www.researchgate.net/publication/350842309_Self-supervised_learning_for_tool_wear_monitoring_with_a_disentangled-variational-autoencoder
researchgate.net
https://twitter.com/fchollet/status/1353421758699687942
twitter.com
https://dl.acm.org/doi/pdf/10.1145/1143844.1143874?casa_token=CSQzAhypHQ0AAAAA:WqAGJXokpttfPIStrcXb_2tXdufgXdDu085FVIBhtQA1hLgXZrJGVHThaTBx4tzGUky8KTRuMJqidg
dl.acm.org
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118432
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