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In the context of deploying a large-scale machine learning project, your team is evaluating the benefits of cloud-based infrastructure over traditional on-premises solutions. The project involves processing vast amounts of data, requires high computational power for model training, and must adhere to strict data compliance standards. Additionally, the project's scale is expected to fluctuate significantly over time. Considering these constraints, which TWO advantages does cloud-based infrastructure specifically offer to address these challenges effectively? Choose the two correct options.
A
Manual resource management allows for precise control over computational resources, ensuring compliance with data standards.
B
The need for continuous investment in on-premises hardware to meet fluctuating computational demands.
C
Scalability to dynamically adjust resources based on the project's current needs, ensuring cost-effectiveness and efficiency.
D
Limited data storage options that enforce strict data compliance by restricting data volume.
E
Flexibility in selecting from a wide range of services and configurations to tailor the infrastructure to specific project requirements, including compliance and computational needs.