Lucie Blechová – Demystifying Anomaly Detection (PyData Prague #25)
Lucie Blechová – Demystifying Anomaly Detection: A Practical Guide for Time Series Data
In this talk, we’ll dive into the essentials of unsupervised anomaly detection for multivariate time series data. As organizations rely increasingly on proactive monitoring, anomaly detection has become vital across domains—from fraud detection to predictive maintenance. This session will cover key challenges in anomaly detection, including data drift, dimensionality, and lack of labeled data. We’ll explore foundational techniques and algorithms, from traditional statistical methods to state-of-the-art machine learning models, offering guidance on selecting tools, setting evaluation metrics, and applying these concepts in real-world scenarios.
Presented at PyData Prague #25 – Moon Time Anomaly (4.2.2025 at similarweb)
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