A Breakdown of Deep Learning Frameworks - KDnuggets

A deep learning framework is a software package used by researchers and data scientists to design and train deep learning models. The idea with these frameworks is to allow people to train their models without digging into the algorithms underlying deep learning, neural networks, and machine learning. These frameworks offer building blocks for designing, training, and validating models through a high-level programming interface. Widely used deep learning frameworks such as PyTorch, TensorFlow, MXNet, and others can also use GPU-accelerated libraries such as cuDNN and NCCL to deliver high-performance multi-GPU accelerated training. An open-source software library created by Google, TensorFlow is a popular tool for machine learning, especially for training deep neural networks.