From fraud and security threat detection to flagging abnormalities in healthcare imaging data, there are countless business applications for automatic identification of abnormal data. This process can be challenging, especially when working with large, complex data. This talk explores deep learning approaches (Sequence models, VAEs, GANs) for anomaly detection, when to use them, performance benchmarks and product possibilities.
