Tag: anomaly-detection

I developed an anomaly detection system for Automattic internal dashboard. When presenting this system (“When good enough is just good enough”), I used to tell that in our particular case, the cost of false alerts was almost zero. I used to explain this claim by the fact that no automatic decisions were made based on the alerts, and that the only subscribers of the alert messages were a limited group of colleagues of mine. Automattic CFO, Stu West, who was the biggest stakeholder in this project, asked me not to stop claiming the “zero cost” claim. When the CFO of the company you work for asks you to do something, you comply. So, I stopped saying “zero cost” but I still listed the error costs as a problem I can safely ignore for the time being. I didn’t fully believe Stu, which is evident from the speaker notes of my presentation deck:

Two months ago, on the PyCon-IL conference, I gave a lecture called “Time Series Analysis: When “Good Enough” is Good Enough”. You may find the written version of this talk here. Today, the conference organizers published all the conference talks on YouTube. Here’s mine:

My today’s talk at PyCon Israel in a post format.

On June 12th, I’ll be talking about anomaly detection and future forecasting when “good enough” is good enough. This lecture is a part of PyCon Israel that takes place between June 11 and 14 in the Bar Ilan University. The conference agenda is very impressive. If “python” or “data” are parts of your professional life, come to this conference!