Introduction to Anomaly Detection with a Convolutional Auto-Encoder on Time Series transformed into Images
Posted Aug 4, 2020, 11:40 AM UTC
10711
This is awesome, thank you for putting this together and posting it :)
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Thanks ! :)
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Awesome!
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Thanks a lot !
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Is this electricity usage or water usage?
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Not exactly. Connection to a website. But yes, we have the typical form of a time series produced by a human use :)
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Cool, I work with water data and I use a 1d CNN to classify leaks in the network. This method looks very useful.
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Nice
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Any paper, blog reference for more depth analysis?
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[deleted]
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To continue the tutorial I had presented here: First Tutorial
Here is a notebook to understand how to detect anomalies on time series.
https://github.com/JulienAu/Anomaly_Detection_Tuto/blob/master/AD_ConvAE_English.ipynb
You can view the notebook on: NbViewer
I'll continue to improve the github in the future. Feel free to ask questions or comment.
I see you've posted a GitHub link to a Jupyter Notebook! GitHub doesn't render large Jupyter Notebooks, so just in case, here is an nbviewer link to the notebook:
https://nbviewer.jupyter.org/url/github.com/JulienAu/Anomaly_Detection_Tuto/blob/master/AD_ConvAE_English.ipynb
Want to run the code yourself? Here is a binder link to start your own Jupyter server and try it out!
https://mybinder.org/v2/gh/JulienAu/Anomaly_Detection_Tuto/master?filepath=AD_ConvAE_English.ipynb
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