Neural networks are now applied across the spectrum of AI applications while deep learning is reserved for more specialized or advanced AI use cases. Written by eWEEK content and product ...

Neural architecture search promises to speed up the process of finding neural network architectures that ... along with feature engineering, transfer learning, and hyperparameter optimization.

AI simulates thinking but lacks intentional or emotional awareness. AI will continue to be limited by binary logic and ...

Deep learning is a subset of machine learning ... is learning complex features about an image. The most common neural network architecture that is used for images is Convolutional Neural Network ...

As next-generation mobile networks grow more complex, high-density 5G environments are placing enormous pressure on co ...

Deep learning networks mostly use neural network architectures and are hence often referred to as deep neural networks. The word “deep” refers to the number of hidden layers in the neural network.

“This knowledge underpins common sense and allows ... But our work suggests otherwise.” The deep learning pioneers believe that better neural network architectures will eventually lead to ...

While achieving notable successes, the intricate architectures and inherent opacity of deep learning neural networks frequently pose challenges to complete mastery, limiting their deployment in ...

we’ll examine the history of neural networks and state-of-the-art approaches to deep learning. Students will learn to design neural network architectures and training procedures via hands-on ...