How to Train TensorFlow Models Using GPUs - DZone AI

In recent years, there has been significant progress in the field of machine learning. Much of this progress can be attributed to the increasing use of graphics processing units (GPUs) to accelerate the training of machine learning models. In particular, the extra computational power has lead to the popularization of deep learning -- the use of complex, multi-level neural networks to create models, capable of feature detection from large amounts of unlabeled training data. GPUs are great for deep learning because the type of calculations they were designed to process are the same as those encountered in deep learning. Images, videos, and other graphics are represented as matrices so that when you perform any operation, such as a zoom-in effect or a camera rotation, all you are doing is applying some mathematical transformation to a matrix.