Training with historical data! Surely, you’re joking says the IoT asset that just got connected

By Priya Sharma – Sr. Data Scientist -IoT Analytics, SAS Institute Inc. Saurabh Mishra – Product Management, IoT, SAS Institute Inc. June 12, 2020 Description: Majority of AI approaches are based on the construct of training against historical data and then inferencing new data. While this is a sound and proven approach, a lot of IoT assets coming online don’t have historical data and we don’t necessarily have the time to wait. Modern Machine Learning methods can be employed to […]

Machine Learning – Anomaly Detection: “Finding a Needle in a Haystack”

After exploring formulation, classification, benchmarking, we explore another facet of Machine Learning: anomaly detection. This part is key in the IoT transformation, as it enables internet-connected AI devices to alert, adapt and respond accordingly. Once properly trained, an IoT could not only warn and prevent imminent failure, but also execute a response, adaptive to the anomaly detected. In this process, we’ll explore intrinsic hurdles that makes the anomaly detection process a non-trivial task of “finding a needle in haystack”. Opportunities abound to explore, and any univariate sequential […]