The first step to a successful ML project is to understand that these projects require different processes, terminology, workflows, and tools than those needed by traditional development.

These projects build on work that a small team at Jefferson Lab began back in 2018 to explore how machine learning techniques could help classify cavity fault data.

Gasiorowski is now a postdoc in SLAC’s machine-learning group, which works with projects across the multi-program national laboratory. Part of his research is working with Terao on analysis tools for ...

Aircraft surface inspections are a critical and mandatory component of airworthiness that uses visual and digital checks to ...

To cope with this complexity, cold-atom physicists have begun exploring ways of using machine learning to augment their experiments. In 2018, for example, a team at the Australian National University ...

Suvendu Mohanty changed from software to ML engineering before the AI boom. Here's how he made the switch — and his advice ...

In this post, we will have listed down the best GPUs for Machine Learning Projects. Go through the list and pick the right one for you.

Here's how to develop an internally facing machine-learning model with a budget of $250,000.