AWS Certified Machine Learning - Specialty
Last Update Dec 11, 2023
Total Questions : 208
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A credit card company wants to build a credit scoring model to help predict whether a new credit card applicant
will default on a credit card payment. The company has collected data from a large number of sources with
thousands of raw attributes. Early experiments to train a classification model revealed that many attributes are
highly correlated, the large number of features slows down the training speed significantly, and that there are
some overfitting issues.
The Data Scientist on this project would like to speed up the model training time without losing a lot of
information from the original dataset.
Which feature engineering technique should the Data Scientist use to meet the objectives?
A company ingests machine learning (ML) data from web advertising clicks into an Amazon S3 data lake. Click data is added to an Amazon Kinesis data stream by using the Kinesis Producer Library (KPL). The data is loaded into the S3 data lake from the data stream by using an Amazon Kinesis Data Firehose delivery stream. As the data volume increases, an ML specialist notices that the rate of data ingested into Amazon S3 is relatively constant. There also is an increasing backlog of data for Kinesis Data Streams and Kinesis Data Firehose to ingest.
Which next step is MOST likely to improve the data ingestion rate into Amazon S3?
A retail company wants to combine its customer orders with the product description data from its product catalog. The structure and format of the records in each dataset is different. A data analyst tried to use a spreadsheet to combine the datasets, but the effort resulted in duplicate records and records that were not properly combined. The company needs a solution that it can use to combine similar records from the two datasets and remove any duplicates.
Which solution will meet these requirements?
A Machine Learning Specialist is attempting to build a linear regression model.
Given the displayed residual plot only, what is the MOST likely problem with the model?
TESTED 11 Dec 2023
