Data Science

Towards Data Science: Use the Drift and Stability of Data to Build More Resilient Models

When building predictive models, model accuracy, measured by metrics like precision, recall and area under the curve (AUC), has traditionally been the primary driver of model design and operationalization. While this leads to high-fidelity model construction at training and testing time, performance in production often degrades, producing results that are worse than expected.

As machine learning (ML) matures within organizations, resiliency often overrides raw predictive accuracy as the defining criterion for operationalizing models. Increasingly, ML practitioners are leaning towards operationalizing well performing, predictable production models rather than those that exhibit high performance at testing but don’t quite deliver on that promise when deployed.

Read the Full Article on Towards Data Science →

Towards Data Science Inc. using Medium, provides a platform for thousands of people to exchange ideas and to expand our understanding of data science. Our audience is mixed, consisting of readers entirely new to the subject and expert professionals who want to share their inventions and discoveries.


Picture of Anindya Datta, Ph.D.

Anindya Datta, Ph.D.

Anindya Datta, the CEO and Chairman of Mobilewalla, is widely regarded as a front-running technologist, leader and innovator, with core contributions to the state of the art in large-scale data management and Internet technologies. Mobilewalla has pioneered audience measurement in mobile apps by applying ground-breaking data science techniques on the industry’s largest volumetric database of mobile app data. Prior to Mobilewalla, Anindya founded and ran Chutney Technologies, where he was backed by Kleiner Perkins and evolved into one of the earliest entrants in the application virtualization area. The company was acquired by Cisco Systems in 2005. Anindya has also been on the faculties of major research universities and institutes in the United States and abroad, including the Georgia Institute of Technology, the University of Arizona, the National University of Singapore and Bell Laboratories. Anindya obtained his undergraduate degree from the Indian Institute of Technology (IIT) Kharagpur, and his MS and Ph.D. degrees from the University of Maryland, College Park.