Autoencoder For Anomaly Detection Using Tensorflow Keras

Autoencoder For Anomaly Detection Using Tensorflow Keras

Autoencoder is an unsupervised neural network model that uses reconstruction error to detect anomalies or outliers. The reconstruction error is the difference between the reconstructed data and the input data. Autoencoder uses only normal data to train the model and all data to make predictions. Therefore, we expect outliers to have higher reconstruction errors because …

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