Which of the following is a benefit of using infrastructure as code (IaC) within machine learning operations (MLOps)?

Infrastructure as Code (IaC) streamlines the deployment of scalable and consistent ML workloads in cloud environments by defining infrastructure resources (like compute, storage, and networking) in code. This allows for automated, repeatable, and version-controlled provisioning, ensuring that ML environments are identical across development, testing, and production, which is crucial for MLOps. IaC does not eliminate hyperparameter tuning; that's a model optimization technique. While IaC can provision powerful instances, it doesn't always do so, nor does it guarantee more accurate models directly. It also doesn't inherently minimize expenses by deploying only low-cost instances; rather, it allows for precise control over resource allocation, which can lead to cost optimization.