AWS Certified AI Practitioner Practice Exam

For an educational game calculating probabilities, which solution requires the least operational overhead?

1. Create a regression model using supervised learning

2. Use reinforcement learning for training a model

3. Calculate probability using simple rules

4. Create a density estimation model using supervised learning

The correct answer is: Calculate probability using simple rules

Calculating probabilities using simple rules involves implementing straightforward formulas and logical conditions based on the defined mechanics of the educational game. This method requires minimal setup and ongoing management since it does not involve training a model or managing data pipelines like more complex learning solutions. In contrast, other options, such as creating a regression model or a density estimation model, involve a data preparation phase, training phases that require computational resources, and continuous maintenance to ensure accuracy over time. Similarly, reinforcement learning, while powerful for dynamic environments, also necessitates a substantial investment in defining reward systems, exploration strategies, and potential updates to the model based on interactions, which increases operational overhead. Using simple rules allows for rapid implementation and ease of understanding, making it well-suited for an educational context where the focus might be more on immediate outcomes and less on the intricacies of machine learning processes. This simplicity not only minimizes operational overhead but also ensures that the solution remains adaptable and easy for educational stakeholders to manage.