Autoencoders can be used for anomaly detection by setting limits on the reconstruction error. All "good" data points are within the acceptable error and all 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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