GitHub / kimfoo / Anomaly-detection-of-sensor-data

This project focuses on building a anomaly detection model to detect wafer runs that are anomalous. The dataset does not contain labelled data (anomalous/non-anomalous), therefore an unsupervised learning method is utilised. Python and the Sci-kitLearn machine learning libraries are the primary tools used in this project.

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PURL: pkg:github/kimfoo/Anomaly-detection-of-sensor-data

Topics: anomaly-detection, isolation-forest-algorithm, machine-learning, sensor-data, unsupervised-learning

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• Readme
• Dependencies