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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.
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