While developing an image recognition model using gcp video
ml-engineer-pro video for while developing an image recognition model using PyTorch with the ResNet50 architecture, your code has been successfully tested on a
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While developing an image recognition model using PyTorch with the ResNet50 architecture, your code has been successfully tested on a small subsample using your local laptop. However, your full dataset consists of 200,000 labeled images, and you aim to efficiently scale your training workload while keeping costs low. You have access to 4 V100 GPUs. What steps should you take to achieve this?