Training infrastructure refers to the hardware, software, and networking resources—like GPUs, cloud clusters, and data pipelines—that power machine learning model development. It’s used by data scientists and engineers to efficiently train, test, and iterate complex algorithms. Organizations benefit from faster model deployment, reduced costs, and scalable AI capabilities, enabling innovation across industries.
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