Detecting Time‑Series Anomalies in Embedding Space: A Practical AI Approach
This article presents an embedding‑based method for time‑series anomaly detection in security and anti‑cheat scenarios, explains how to vectorise logs, sample and compute distribution features, details implementation code, and validates the approach with four synthetic experiments showing precision‑recall improvements at day and hour granularity.
