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From mehdi sey <seydali.me...@gmail.com>
Subject Distributed Training in tensorflow
Date Sun, 06 Jan 2019 09:41:36 GMT
Distributed training allows computational resources to be used on the whole
cluster and thus speed up training of deep learning models. TensorFlow is a
machine learning framework that natively supports distributed neural network
training, inference and other computations.Using this ability, we can
calculate gradients on the nodes the data are stored on, reduce them and
then finally update model parameters.In case of TensorFlow on Apache Ignite
does in a server in cluster we must run a tensorflow worker for doing work
on its data?

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