🗓️ Week 09 - Anomaly detection

Theme: Unsupervised Learning

Welcome to the ninth week of this course!

We finish our exploration of unsupervised learning with yet another family of unsupervised learning: anomaly detection. We will explain in which cases anomaly detection applies before introducing a few techniques of anomaly detection (anomaly detection through clustering, a tree-based anomaly detection technique called isolation forest and a density-based anomaly detection technique called Local Outlier Factor (LOF), one-class SVM and autoencoders).

👩🏻‍🏫 Lecture Material

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To minimize setup issues and allow for faster execution times, this week’s lecture notebook (LSE_DS202A_2025_2026_W09_lecture.qmd) can be found on Nuvolos.