Machines fail. By creating a time-series prediction model from historical sensor data, you can know when that failure is coming Anomaly detection covers a large number of data analytics use cases.

Time-series data represents one of the most challenging data types for businesses and data scientists. The data sets are often very big, change continuously, and are time-sensitive by nature. One ...

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...

Lacework added an automated time-series modeling to its existing anomaly detection capabilities and enhanced its alert system for better threat detection and investigation at scale. Polygraph then ...

CUPERTINO, Calif.--(BUSINESS WIRE)--Falkonry today announced an automated anomaly detection application called Falkonry Insight which operates on high-speed sensor time series data. Insight is the ...