In distributed training, the workload is shared between mini processors called the worker nodes. The nodes run in parallel to speed up the model training. Traditionally, distributed training has been used for machine learning models.  But of late, it’s making inroads into compute-intensive tasks such as deep learning to train deep neural networks. Below, we…

The post Top Distributed Training Frameworks In 2021 appeared first on Analytics India Magazine.