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In the context of machine learning model deployment, how can Docker be utilized to enhance the process?
Correct Answer: B
Docker is a containerization platform that ensures consistent environments for machine learning model training and inference by packaging dependencies, libraries, and configurations into portable containers. NVIDIA's documentation on deploying models with Triton Inference Server and NGC (NVIDIA GPU Cloud) emphasizes Docker's role in eliminating environment discrepancies between development and production, ensuring reproducibility. Option A is incorrect, as Docker does not generate features. Option C is false, as Docker does not reduce computational requirements. Option D is wrong, as Docker does not affect model accuracy. References: NVIDIA Triton Inference Server Documentation: https://docs.nvidia.com/deeplearning/triton-inference-server /user-guide/docs/index.html NVIDIA NGC Documentation: https://docs.nvidia.com/ngc/ngc-overview/index.html