The transformer model has become one of the main highlights of advances in deep learning and deep neural networks.

A new computing architecture enables advanced machine-learning computations to be performed on a low-power, memory-constrained edge device. The technique may enable self-driving cars to make ...

Learn More. Deep learning is a subset of machine learning that uses neural networks with multiple layers to model complicated patterns and representations in data.

Quantity and quality of data are not enough to take full advantage of machine learning. The structures built around data -- and the way data is structured -- influence the value you can derive ...

Deep learning is based on the representation learning (or feature learning) branch of machine learning theory. By extracting high-level, complex abstractions as data representations through a ...

Neural architecture search promises to speed up the process of finding neural network architectures that will yield good models for a given dataset.

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases.

Every machine learning engineer deals with systems that have hyperparameters, and the most basic task in automated machine learning (AutoML) is to automatically set these hyperparameters to optimize ...