Topic 1 Question 119

AWS Certified Machine Learning - Specialty

Topic 1 Question 119
A data scientist wants to use Amazon Forecast to build a forecasting model for inventory demand for a retail company. The company has provided a dataset of historic inventory demand for its products as a .csv file stored in an Amazon S3 bucket. The table below shows a sample of the dataset. How should the data scientist transform the data?
- Use ETL jobs in AWS Glue to separate the dataset into a target time series dataset and an item metadata dataset. Upload both datasets as .csv files to Amazon S3.
- Use a Jupyter notebook in Amazon SageMaker to separate the dataset into a related time series dataset and an item metadata dataset. Upload both datasets as tables in Amazon Aurora.
- Use AWS Batch jobs to separate the dataset into a target time series dataset, a related time series dataset, and an item metadata dataset. Upload them directly to Forecast from a local machine.
- Use a Jupyter notebook in Amazon SageMaker to transform the data into the optimized protobuf recordIO format. Upload the dataset in this format to Amazon S3.
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コメント(6)
- I would answer A. Target and metadata must be in two files and loaded from S3, based on documentation: https://docs.aws.amazon.com/forecast/latest/dg/dataset-import-guidelines-troubleshooting.html
  
  👍 26
  joep212021/09/26
- 正解だと思う選択肢: A
  Amazon Forecast requires the input data to be separated into a target time series dataset and an item metadata dataset.
  
  The target time series dataset should include the time series data that you want to use for forecasting, such as inventory demand in this case. The item metadata dataset should include the metadata that describes the items in the time series, such as product IDs, categories, and attributes.
  
  Therefore, the data scientist should use ETL jobs in AWS Glue to separate the dataset into a target time series dataset and an item metadata dataset. Both datasets should be uploaded as .csv files to Amazon S3, which is a suitable storage option for input data to Amazon Forecast.
  
  👍 5
  AjoseO2023/03/22
- 正解だと思う選択肢: A
  I would vote for A
  
  👍 3
  ystotest2022/11/24
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