Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine-learning model might think it is a new data point. In computer science ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

AI is not limited to diagnostics or imaging. It also plays a transformative role in biomedical research, computational ...

A recent study applied machine learning to medical and pharmacy claims data to develop a model for predicting hidradenitis suppurativa (HS) diagnosis, highlighting the potential for improved ...

Trading used to be about gut feelings and reading charts. Traders sat at desks watching screens, trying to spot patterns that meant prices would go up or down. That world exists still but machines can ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

Inspired by how the human brain consolidates memory, the 'Nested Learning' framework allows different parts of a model to learn and update at different speeds.

At James Hardie, where Truong served as CEO from 2018 to 2021, he transformed a business-to-business building materials supplier into a consumer-focused brand. The company's market capitalization grew ...

Periodic maintenance is common too, but still inefficient and often based on time, not actual machine condition. That ...