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. It’s your job to do the anomaly detection. it is streamlits job to display your data interactively.

1 Like

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

No. I’m here to learn about streamlit specifically. I don’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.

2 Likes