Exam AWS Certified Machine Learning - Specialty All Questions

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Exam AWS Certified Machine Learning - Specialty topic 1 question 119 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty

Question #: 119
Topic #: 1

[All AWS Certified Machine Learning - Specialty Questions]

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?

A. 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.
B. 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.
C. 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.
D. 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.

Show Suggested Answer

Suggested Answer: A 🗳️

by [deleted] at Feb. 5, 2021, 7:45 p.m.

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Highly Voted 3 years, 3 months ago

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

upvoted 26 times

ZSun

1 year, 8 months ago

1. I cannot find any evidence support the seperate file defination. 2. A,B,C all seperate datasets, this explanation is weak.

upvoted 1 times

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AjoseO

Highly Voted 1 year, 9 months ago

Selected Answer: 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.

upvoted 9 times

ccpmad

1 year, 4 months ago

thank you chatgpt

upvoted 2 times

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AIWave

Most Recent 10 months, 1 week ago

I would go with A Input formats for forecast -> Json, CSV and paraquet (Selects A & eliminates B, C, D) Data needs to be split in target time series dataset and an item metadata dataset

upvoted 1 times

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Mickey321

1 year, 4 months ago

Selected Answer: A

Target and metadata must be in two files

upvoted 1 times

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kaike_reis

1 year, 4 months ago

Selected Answer: A

Letter A is correct, as it uses a specific transformation service (AWS Glue) and saves it in a cloud database for AWS Forecast to access. By default in ML, our storage option will be AWS S3 (unless caveats or issue specifications). That said, we discard B and C. Letter D is discarded due to the format requested by AWS Forecast being csv.

upvoted 1 times

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ystotest

2 years, 1 month ago

Selected Answer: A

I would vote for A

upvoted 3 times

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tgaos

2 years, 7 months ago

The answer is A. According to the https://docs.aws.amazon.com/forecast/latest/dg/forecast.dg.pdf , page 51. Target Time Series Dataset: Required: timestamp, item_id, demand Additional: lead_time Item Metadata Dataset: item_id, category

upvoted 3 times

tgaos

2 years, 6 months ago

You can find the same question with the picture at https://ccnav7.net/a-data-scientist-wants-to-use-amazon-forecast-to-build-a-forecasting-model-for-inventory-demand-for-a-retail-company/

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DSJingguo

3 years, 2 months ago

The correct answer is A ''Forecast supports only the comma-separated values (CSV) file format. You can't separate values using tabs, spaces, colons, or any other characters. Guideline: Convert your dataset to CSV format (using only commas as your delimiter) and try importing the file again.''

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achiko

3 years, 2 months ago

lead time belongs to related time series, as its not a target variable

upvoted 1 times

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