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.
You are building a data pipeline on Google Cloud. You need to prepare data using a casual method for a machine-learning
-
answerhappygod
- Site Admin
- Posts: 899604
- Joined: Mon Aug 02, 2021 8:13 am
You are building a data pipeline on Google Cloud. You need to prepare data using a casual method for a machine-learning
Join a community of subject matter experts. Register for FREE to view solutions, replies, and use search function. Request answer by replying!