Systems | Development | Analytics | API | Testing

February 2021

Concept Drift Deep Dive: How to Build a Drift-Aware ML System

There is nothing permanent except change. In a world of turbulent, unpredictable change, we humans are always learning to cope with the unexpected. Hopefully, your machine learning business applications do this every moment, by adapting to fresh data. In a previous post, we discussed the impact of COVID-19 on the data science industry.

Accelerating ML Deployment in Hybrid Environments

We’re seeing an increase in demand for hybrid AI deployments. This trend can be attributed to a number of factors. First of all, many enterprises look to hybrid solutions to address data locality, in accordance with a rise in regulation and data privacy considerations. Secondly, there is a growing number of smart edge devices powering innovative new services across industries.