In the realm of machine learning frameworks, there’s no one-size-fits-all solution. PyTorch and TensorFlow offer distinct advantages that cater to different aspects of the machine learning workflow.

Size is king, however ... deep learning applications will increasingly be written and deployed with PyTorch. TensorFlow isn’t dead. It’s just not as popular as it once was.

Both PyTorch and TensorFlow support deep learning and transfer ... because it is relatively rare to have a data set of sufficient size. Instead, it is common to pretrain a ConvNet on a very ...

As the popularity of the Python programming language persists, a user survey of search topics identifies a growing focus on AI and machine learning tasks and, with them, greater adoption of related ...

This article will discuss the seven popular tools and frameworks used for developing AI applications: TensorFlow, PyTorch, Keras, Caffe, Microsoft Cognitive Toolkit, Theano and Apache MXNet.