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.

Machine learning as a tool in theoretical science Machine learning methods relying on synthetic data are starting to be used in mathematics and theoretical physics.

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

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 ...

Using PyTorch to streamline machine-learning projects A platform that lets surgeons browse videos of past operations has found a way to make its machine learning more effective.

Tweaking machine learning algorithms and models won't always be for experts only, thanks to these cutting-edge projects ...

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.

Similar analogies exist in the area of autonomous vehicles. Overall, machine learning seems to define the notion of probabilistic algorithms in computer science in a similar manner as quantum physics.

Use modern machine learning tools and python libraries. Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how ...