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 ...

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 ...

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

Deep learning, a subset of machine learning, refers to machine learning that takes place on artificial intelligence neural networks.

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 ...

Deep Learning is not only a massive buzzword spanning business and technology but also a concept that will transform most industries and jobs, as well as the way we live our lives. However, there ...

Deep learning's availability of large data and compute power makes it far better than any of the classical machine learning algorithms.

Deep-learning theory shows that deep nets have two different exponential advantages over classic learning algorithms that do not use distributed representations 21.