Autoencoders can be used for anomaly detection by setting limits on the reconstruction error. All ‘good’ data points fall within the acceptable error and any outliers are considered anomalies. This approach can be used for images or other forms of data. This video tutorial explains the process using a synthetic dataset stored in a csv file.

The code from this video is available at: https://github.com/bnsreenu/python_for_microscopists

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