Get to know the team behind the Enterprise AI Lab!
Our data scientists publish about their latest projects
(in and out of the Lab) in Data from the Trenches.
Causal Inference on Observational Data: It's All About the Assumptions
Previously, we showed that uplift modeling, a causal inference success story for businesses, can outperform more conventional churn model...
Jun 03, 2021 / Read More
Enterprise Causal Inference: Beyond Churn Modeling
As machine learning practitioners, we often want to investigate what-if scenarios from our newly trained ML models. For example (and perh...
Apr 28, 2021 / Read More
The Potential for Using Deep Learning to Improve Local Weather Forecasts
ALMA, the Atacama Large Millimeter /submillimeter Array, is currently the largest radio telescope in the world. The observatory is the re...
Mar 18, 2021 / Read More
Deploying ML Models for Edge Computing on Drones
In this post, we will detail how we designed and trained a single shot detector (SSD) model that allows unmanned aerial vehicles powered ...
Mar 10, 2021 / Read More
Why Is My Data Drifting?
Machine learning (ML) models deployed in production are usually paired with systems to monitor possible dataset drift. MLOps systems are ...
Dec 02, 2020 / Read More
Measuring Models’ Uncertainty with Conformal Prediction
Oct 01, 2020 / Read More
Making Neural Networks Smaller for Better Deployment
There is a clear trend in the data science and machine learning industry on training bigger and bigger models. These models achieve near-...
Jul 30, 2020 / Read More