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Anomaly Detection using Autoencoder Neural Networks

Autoencoders are deep neural networks that learn to predict compressed versions of their inputs. model.fit(x_train, x_train)
The number of neurons in the middle layers are usually set to be fewer than the number of input neurons, so that the network learns just the essential information in the inputs.

Application areas include Anomaly Detection, Image Denoising, etc.

Instructions

To run the app, the streamlit package needs to be installed. Download the repository and install from requirements.txt, then run the following command to start a local streamlit app session.

streamlit run app.py

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