Detecting anomalies in time series data has become an interesting field of research over the last several decades. This field detects irregular or unexpected patterns throughout time intervals; patterns that often contain meaningful information and may even indicate threats or erratic behaviors in various scenarios and applications. Here at Slice, we detect anomalies present in abnormal receipt transaction counts and price irregularities for merchants over time. Some of these anomalies are critical and require urgent identification and processing, so we can ensure high-quality data products to delight our clients.
Topics: Neural Networks, Deep Learning