Topic 1 Question 77
An ML engineer normalized training data by using min-max normalization in AWS Glue DataBrew. The ML engineer must normalize the production inference data in the same way as the training data before passing the production inference data to the model for predictions. Which solution will meet this requirement?
Apply statistics from a well-known dataset to normalize the production samples.
Keep the min-max normalization statistics from the training set. Use these values to normalize the production samples.
Calculate a new set of min-max normalization statistics from a batch of production samples. Use these values to normalize all the production samples.
Calculate a new set of min-max normalization statistics from each production sample. Use these values to normalize all the production samples.
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コメント(2)
- 正解だと思う選択肢: B
Models are sensitive to data distribution. Consistency needed for accurate predictions and hence Option-B keeping the same min-max normalization statistics will help; Option C & D affect model performance; Option-A introduces inconsistency
👍 2Saransundar2024/12/03 - 正解だと思う選択肢: B
To ensure reliable and accurate model predictions, it's essential to use the same min-max normalization statistics from the training data.
👍 1GiorgioGss2024/11/28
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