Shreya Khurana
I'm a data scientist at Intuit in California, USA and I work on the anomaly detection capability that tracks authentication and business health metrics at Intuit. I was previously building NLP models at GoDaddy, but I enjoy working with data in general. I'm a Python enthusiast and enjoy sharing my learnings with the community - I've previously presented at the Grace Hopper Conference, PyCon US, EuroPython, and GeoPython. When not opposite a screen, I can be found frolicking in nature and exploring new trails.
Sessions
Anomaly detection is hardly a new problem, nor is the progress in it as rapid as the LLM blast we’re witnessing today. But it is pressing.
In this talk, we’ll talk about a realtime anomaly detection pipeline on time series data and discuss the nitty-gritties of the algorithm knobs that help us build an unbiased and reliable system, which includes 1) using NeuralProphet, an open source framework, to forecast for time series data and 2) using robust techniques to detect true anomalies using forecasting errors.