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NEW QUESTION 42
You have built a machine model to predict whether a bank customer is going to default on a loan. You want to use Local Interpretable Model-Agnostic Explanations (LIME) to understand a specific prediction. What is the key idea behind LIME?

• A. Model-agnostic techniques are more interpretable than techniques that are dependent on the types of models.
• B. Local explanation techniques are model agnostic, while global explanation techniques are not.
• C. Global behavior of a machine learning model may be complex, while the local behavior may be approximated with a simpler surrogate model.
• D. Global and local behaviors of machine learning models are similar.

Answer: C

NEW QUESTION 43
What preparation steps are required to access an Oracle AI service SDK from a Data Science notebook session?

• A. Import the REST API
• B. Create and upload the API signing key and config file
• C. Call the Accented Data Science (ADS) command to enable Al integration
• D. Create and upload execute.py and runtime.yaml

Answer: B

NEW QUESTION 44
You have a complex Python code project that could benefit from using Data Science Jobs as it is a repeatable machine learning model training task. The project contains many subfolder and classes. What is the best way to run this project as a job?

• A. ZIP the entire code project folder and upload it as a Job artifact on job creation, Jobs identities the main executable file automatically.
• B. ZIP the entire code project folder and upload it as a Job artifact Jobs automatically identifies
• C. Rewrite your code so that a single executable Python or Bash/Shell script file.
• D. ZIP the entire code project folder, upload it as a Job artifact on job creation and set JOB_RUN_ENTRYPOINT to point to the main executable file.

Answer: D

Explanation:
That main top level where the code is run.

NEW QUESTION 45
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