Google Cloud Professional Machine Learning Engineer — Question 8
You are an ML engineer at a large grocery retailer with stores in multiple regions. You have been asked to create an inventory prediction model. Your model's features include region, location, historical demand, and seasonal popularity. You want the algorithm to learn from new inventory data on a daily basis. Which algorithms should you use to build the model?
Answer options
- A. Classification
- B. Reinforcement Learning
- C. Recurrent Neural Networks (RNN)
- D. Convolutional Neural Networks (CNN)
Correct answer: C
Explanation
Recurrent Neural Networks (RNN) are ideal for processing sequences of data, such as time-series data in inventory prediction, allowing the model to learn from historical patterns and adapt to new information over time. Classification algorithms are not suitable for continuous prediction tasks, while Reinforcement Learning focuses on learning optimal actions through rewards, which is not applicable here. Convolutional Neural Networks (CNN) are primarily used for image processing tasks and do not fit the requirements for inventory prediction.