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: Fault diagnosis plays a pivotal role in ensuring the safety of industrial processes. In the realm of fault diagnosis, stack autoencoders (SAE) have gained widespread popularity for their ...
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