A city wants to monitor its air quality to address the consequences of air pollution. A Machine Learning Specialist needs to forecast the air quality in parts per million of contaminates for the next 2 days in the city. As this is a prototype, only daily data from the last year is available.
Which model is MOST likely to provide the best results in Amazon SageMaker?
A . Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the single time series consisting of the full year of data with a predictor_typeof regressor.
B . Use Amazon SageMaker Random Cut Forest (RCF) on the single time series consisting of the full year of data.
C . Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a predictor_typeof regressor.
D . Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a predictor_typeof classifier.
Answer: C
Explanation:
Reference: https://aws.amazon.com/blogs/machine-learning/build-a-model-to-predict-the-impact-ofweather-on-urban-air-quality-using-amazon-sagemaker/?ref=Welcome.AI
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