I believe an approach to machine learning deployment that’s based on an industry standard, language-agnostic, and able to represent a broad range of algorithms is the clear path forward.

Designed to support the entire machine learning lifecycle -- from data ingestion and model training to deployment and monitoring -- Azure ML is empowering developers to integrate predictive ...

The open-source platform from LF Networking could be a game changer for AI networking applications. Essedum is a specialized ...

Learn how to organize and structure your machine learning projects for real-world deployment. From directory layout to model ...

Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...

Prospective silent deployment and evaluation of an intelligent machine learning model for prediction of emergency department visits during cancer treatment.

Drawing on real-world use cases and my own experience as a leader in this space, I'll describe how cloud-native technologies ...

Citing vulnerabilities and biased outputs in the program, multiple advocacy organizations and nonprofits signed a letter to the Office of Management and Budget asking it to bar Elon Musk’s Grok from ...