machine-learning video for you are an ML Engineer at a financial services company tasked with deploying a machine learning model for real-time fraud detection
You are an ML Engineer at a financial services company tasked with deploying a machine learning model for real-time fraud detection in production. The model requires low-latency inference to ensure that fraudulent transactions are flagged immediately. However, you also need to conduct extensive testing and experimentation in a separate environment to fine-tune the model and validate its performance before deploying it. You must provision compute resources that are appropriate for both environments, balancing performance, cost, and the specific needs of testing and production. Which of the following strategies should you implement to effectively provision compute resources for both the production environment and the test environment using Amazon SageMaker, considering the different requirements for each environment? (Select two)