A Breakdown of Deep Learning Frameworks


What is a Deep Learning Framework? 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.