If you’re a data scientist or you work with machine learning (ML) models, you have tools to label data, technology environments to train models, and a fundamental understanding of MLops and modelops.

Why is machine learning so hard to explain? Making it clear can help with stakeholder buy-in Your email has been sent Getty Images/iStockphoto More must-read AI coverage ‘Catastrophic’ Stakes: OpenAI ...

Sometimes, the best way to examine something is in the context of stuff you already know a little bit about. Or, at least, think you do. Writers, especially journalists, tend to lean on metaphor and ...

The resurgence of artificial intelligence (AI) is largely due to advances in pattern-recognition due to deep learning, a form of machine learning that does not require explicit hard-coding. The ...

This special series focuses on important community issues, innovative solutions to societal challenges, and people and non-profit groups making an impact through technology. by Lisa Stiffler on Mar 16 ...

You're currently following this author! Want to unfollow? Unsubscribe via the link in your email. Follow Dan DeFrancesco Every time Dan publishes a story, you’ll get an alert straight to your inbox!