Study compares machine learning models of raindrop formation

Raindrops form inside clouds when tiny particles of water collide and stick together, forming larger droplets that eventually ...
RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...

First-ever black hole image sharpened using machine learning

The historic first image of the Messier 87 (M87) supermassive black hole, captured using the Event Horizon Telescope, has been sharped using a machine learning technique called PRIMO. PRIMO is short ...
YouTube on MSN

Tracking your EV, solar, and energy use with machine learning - Sense smart home interview

Explore how machine learning enhances energy monitoring in smart homes with CEO Mike Phillips from Sense. This interview covers the application of AI in tracking energy use, detecting potential device ...
Colgate University

Picker ISI Training Workshop Helps Apply AI-Powered Machine Learning Skills for Research

More than 20 faculty members and several students from across academic disciplines attended a two-day training workshop on June 4–5 to learn how AI machine-learning skills can assist with their ...

Learn How Businesses Are Using AI to Reduce Expenses With This $20 Hands-On Training

Build real-world automation skills using ChatGPT, machine learning concepts, and practical workflow strategies.
Quanta Magazine

What Is Machine Learning?

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

SAS puts machine learning in marketers' hands with new SAS 360 Marketing AI

SAS, the leader in data and AI, today announced SAS 360 Marketing AI, a new solution to help marketers build, deploy and scale machine learning models without relying on overstretched data science ...