Anomaly Detection Algorigthms

I am looking to implement anomaly detection algorithms to detect performance issues after running a load test.

Is there any built-in functions already available within Streamlit or I need to leverage other open source libraries such as PyOD.

Please enlighten me :slight_smile:

streamlit is a GUI layer. Think of it like a real time jupyter-notebook with all the code hidden by default and flexible caching and a ton of options for visualization.

With that in mind. Anomaly detection has very little to do with streamlit, and more to do with statistical analysis. Itโ€™s your job to do the anomaly detection. it is streamlits job to display your data interactively.

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Thanks @conic, can you please suggest open source libraries to detect the anomalies.

No. Iโ€™m here to learn about streamlit specifically. I donโ€™t think this is a good place to ask about anomaly detection. Anomaly detection has very little to do with streamlits baseline functionality.

After a bit of googling I found a different forum for AI and ML:

Ask there.

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