Free GARP RAI Exam Questions

A company wants to apply reinforcement learning to manage its warehouse inventory, learning when to restock based on demand fluctuations. What is a potential drawback of using reinforcement learning in this scenario?

During training, an RNN model used for forecasting exhibits extremely high gradients at certain steps, causing instability in learning. Which of the following best describes this problem?

A retail bank uses self-training to classify loan applicants as high or low risk, but it finds that updating the model after each new labeled data point is computationally intensive. Which approach can the bank use to reduce this burden?

A trading firm uses reinforcement learning to determine the best time to buy or sell an asset. They have partial information about the state transitions and aim to maximize long-term profits by identifying the best action in each state. Which reinforcement learning approach is most suitable for this scenario?

What is a primary reason to remove duplicate observations during data cleaning?