Artificial Neural Networks are a fundamental part of Deep Learning. They are mathematical models of biological neural networks based on the concept of artificial neurons.

Both PyTorch and TensorFlow support deep learning and transfer learning. Transfer learning, which is sometimes called custom machine learning, starts with a pre-trained neural network model and ...

Discover the best deep learning software for training and deploying neural networks with powerful features and customizable options. Written by eWEEK content and product recommendations are ...

At version r1.5, Google's open source machine learning and neural network library is more capable, more mature, and easier to learn and use If you looked at TensorFlow as a deep learning framework ...

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

Sponsored Post Researchers at Google and Intel recently collaborated to extract the maximum performance from Intel® Xeon and Intel® Xeon Phi processors running TensorFlow*, a leading deep learning and ...

Many deep-learning models are too large to run on mobile devices; for example, the research team could not run the VGG-19 model on their mobile device.

The neural network uses this training data to extract and assign weights to features that are unique to fruits labelled good, such as ideal size, shape, color, consistency of color and so on.