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Answer Posted / Mr Sonu Kumar
Distributed Training in TensorFlow refers to a method of training neural networks across multiple CPUs, GPUs, or TPUs within a single machine or across multiple machines. This approach allows for faster training times on large datasets by distributing the computational load.
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