Free GARP RAI Exam Questions

Which of the following scenarios represents a binary classification problem?

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 tech firm is evaluating different models for an NLP project requiring high computational efficiency and parallel processing. Why might transformers be more suitable than RNNs for this task?

An insurance company is using a neural network for classifying claims as "Fraudulent" or "Non-Fraudulent." They decide to use ReLU (Rectified Linear Unit) as the activation function for the hidden layers. What is the primary purpose of using an activation function like ReLU in this neural network?

A data scientist is tuning the ridge regression model’s hyperparameter, λ, to control the trade-off between model fit and complexity. If λ is set too high, what effect is most likely?