One can’t read any news today without a barrage of articles about data science and machine learning and artificial intelligence. Just recently, Jeff Bezos opened up his private MARS (Machine Learning, ...

Demand forecasting methods have been used in retail for a long time. Most of them are based on historical data, which is no longer useful in the new COVID-19 reality. If you used an ML-powered demand ...

A new research paper shows the approach performs significantly better than the random-walk forecasting method.

Forecasting macroeconomic variables is key to developing a view on a country's economic outlook. Most traditional forecasting models rely on fitting data to a pre-specified relationship between input ...

We develop a framework to nowcast (and forecast) economic variables with machine learning techniques. We explain how machine learning methods can address common shortcomings of traditional OLS-based ...

Picture a single forecasting mistake triggering a cascade of negative consequences, such as surplus inventory, strained supplier relationships and disappointed customers. In today's world, accurate ...

An operational solar farm in Australia, where the study took place. Image: Nextracker. Machine learning techniques have been used in a study to boost the accuracy of renewables forecasts by up to 45%, ...

In a new study led by the University of Washington, researchers have demonstrated artificial intelligence's ability to improve lightning forecasts. Lightning strikes led to the devastating California ...