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Answer: Merging various datasets., Eliminating records with missing values.
The correct answers are C and E. During the data ingestion and preparation phase in Azure Machine Learning, it is common to combine multiple datasets (Option C) to ensure comprehensive data for model training. Additionally, data cleaning processes such as removing records with missing values (Option E) are essential to maintain quality and integrity. Calculating the model's accuracy (Option A) and scoring test data (Option B) typically occur in later phases like model evaluation, and deploying the model for real-time predictions (Option D) happens during the deployment phase.
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In the Azure Machine Learning process, identify the two key actions that occur during the data ingestion and preparation phase.
A
Calculating the model's accuracy.
B
Scoring the test data with the model.
C
Merging various datasets.
D
Deploying the model for real-time predictions.
E
Eliminating records with missing values.