You are building a data pipeline on Google Cloud. You need to prepare data using a casual method for a machine-learning
Posted: Mon Aug 01, 2022 9:50 am
You are building a data pipeline on Google Cloud. You need to prepare data using a casual method for a machine-learning process. You want to support a logistic regression model. You also need to monitor and adjust for null values, which must remain real-valued and cannot be removed. What should you do?
A. Use Cloud Dataprep to find null values in sample source data. Convert all nulls to "˜none' using a Cloud Dataproc job.
B. Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 0 using a Cloud Dataprep job. Most Voted
C. Use Cloud Dataflow to find null values in sample source data. Convert all nulls to "˜none' using a Cloud Dataprep job.
D. Use Cloud Dataflow to find null values in sample source data. Convert all nulls to 0 using a custom script.
A. Use Cloud Dataprep to find null values in sample source data. Convert all nulls to "˜none' using a Cloud Dataproc job.
B. Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 0 using a Cloud Dataprep job. Most Voted
C. Use Cloud Dataflow to find null values in sample source data. Convert all nulls to "˜none' using a Cloud Dataprep job.
D. Use Cloud Dataflow to find null values in sample source data. Convert all nulls to 0 using a custom script.