Anomaly detection is the process of finding items in a dataset that are different in some way from the majority of the items. For example, you could examine a dataset of credit card transactions to ...
If the dataset has no fraud examples, we can use either the outlier detection approach using isolation forest technique or anomaly detection using the neural autoencoder. After the machine learning ...
The Data Science Lab Autoencoder Anomaly Detection Using PyTorch Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a ...
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