AWS Certified Machine Learning – Specialty — Question 60

A large consumer goods manufacturer has the following products on sale:
* 34 different toothpaste variants
* 48 different toothbrush variants
* 43 different mouthwash variants
The entire sales history of all these products is available in Amazon S3. Currently, the company is using custom-built autoregressive integrated moving average
(ARIMA) models to forecast demand for these products. The company wants to predict the demand for a new product that will soon be launched.
Which solution should a Machine Learning Specialist apply?

Answer options

• A. Train a custom ARIMA model to forecast demand for the new product.
• B. Train an Amazon SageMaker DeepAR algorithm to forecast demand for the new product.
• C. Train an Amazon SageMaker k-means clustering algorithm to forecast demand for the new product.
• D. Train a custom XGBoost model to forecast demand for the new product.

Correct answer: B

Explanation

The Amazon SageMaker DeepAR algorithm is specifically designed for time series forecasting and is well-suited for predicting demand in scenarios like this, where there are multiple related products. The other options, such as custom ARIMA models and XGBoost, are either less efficient for this specific purpose or not ideally suited for demand forecasting compared to DeepAR.