1. Demand Prediction Engine: A Technological Leap from "Passive Response" to "Active Anticipation" ...

Today’s data scientists and machine learning engineers now have a wide range of choices for how they build models to address the various patterns of AI for their particular needs.

Machine learning models should be trained and tested on separate data. A new study assesses the effect on model performance when this boundary is blurred.

While building machine learning models is fundamental to today’s narrow applications of AI, there are a variety of different ways to go about realizing the same ends. So-called machine learning ...

What goes into a machine learning sandwich Machine learning engineering happens in three stages — data processing, model building and deployment and monitoring.

The ADB–Cornell study finds that machine learning poverty maps often misfire, overestimating welfare in poor, rural, ...