This project shows how to find anomalies in financial time series data, specifically the stock values of Apple (AAPL), using a LSTM Autoencoder. Stock price anomalies may be a sign of major market ...
Abstract: The growth of interconnected devices has led to an enormous volume of temporal data that requires specialized compression models for efficient storage. Besides this, most applications need ...
Abstract: Autoencoders have been extensively used in the development of recent anomaly detection techniques. The premise of their application is based on the notion that after training the autoencoder ...
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