Explainable AI Market Will Reach $34.6 Billion by 2033 - Interview Kickstart's Adds XAI Specialization to Machine Learning Course

SANTA CLARA, CA - October 30, 2025 - - The global demand for Explainable AI (XAI) is accelerating as organizations seek ...
CoinTelegraph

5 Python libraries to interpret machine learning models

Python libraries that can interpret and explain machine learning models provide valuable insights into their predictions and ensure transparency in AI applications. A Python library is a collection of ...

Cengage Work Expands AI and Cybersecurity Training Reach Through LinkedIn Learning

Cengage Work expands partnership with LinkedIn Learning through its cybersecurity education provider, Infosec Institute.

Machine learning workflow enables faster, more reliable organic crystal structure prediction

Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals ...
InfoWorld

Time series forecasting with XGBoost and InfluxDB

XGBoost is a popular open source machine learning library that can be used to solve all kinds of prediction problems. Here’s how to use XGBoost with InfluxDB. XGBoost is an open source machine ...
National Academies

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, ...
EurekAlert!

Brigham researchers use machine learning to improve cardiovascular risk assessment

Risk calculators are used to evaluate disease risk for millions of patients, making their accuracy crucial. But when national models are adapted for local populations, they often deteriorate, losing ...
The Harvard Crimson

SEAS Researchers Develop Wearable Sensor System to Measure Running Forces Outdoors

Researchers at the School of Engineering and Applied Sciences have developed a wearable sensor system capable of estimating ...
Science Daily

Researchers use machine learning to improve cardiovascular risk assessment

Researchers used advanced machine learning to increase the accuracy of a national cardiovascular risk calculator while preserving its interpretability and original risk associations. Risk calculators ...