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Question 299 - MLS-C01 discussion

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A company wants to use machine learning (ML) to improve its customer churn prediction model. The company stores data in an Amazon Redshift data warehouse.

A data science team wants to use Amazon Redshift machine learning (Amazon Redshift ML) to build a model and run predictions for new data directly within the data warehouse.

Which combination of steps should the company take to use Amazon Redshift ML to meet these requirements? (Select THREE.)

A.

Define the feature variables and target variable for the churn prediction model.

Answers
A.

Define the feature variables and target variable for the churn prediction model.

B.

Use the SQL EXPLAIN_MODEL function to run predictions.

Answers
B.

Use the SQL EXPLAIN_MODEL function to run predictions.

C.

Write a CREATE MODEL SQL statement to create a model.

Answers
C.

Write a CREATE MODEL SQL statement to create a model.

D.

Use Amazon Redshift Spectrum to train the model.

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D.

Use Amazon Redshift Spectrum to train the model.

E.

Manually export the training data to Amazon S3.

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E.

Manually export the training data to Amazon S3.

F.

Use the SQL prediction function to run predictions,

Answers
F.

Use the SQL prediction function to run predictions,

Suggested answer: A, C, F

Explanation:

Amazon Redshift ML enables in-database machine learning model creation and predictions, allowing data scientists to leverage Redshift for model training without needing to export data.

To create and run a model for customer churn prediction in Amazon Redshift ML:

Define the feature variables and target variable: Identify the columns to use as features (predictors) and the target variable (outcome) for the churn prediction model.

Create the model: Write a CREATE MODEL SQL statement, which trains the model using Amazon Redshift's integration with Amazon SageMaker and stores the model directly in Redshift.

Run predictions: Use the SQL PREDICT function to generate predictions on new data directly within Redshift.

Options B, D, and E are not required as Redshift ML handles model creation and prediction without manual data export to Amazon S3 or additional Spectrum integration.

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asked 31/10/2024
Helania Stevenson
51 questions
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