You are a data scientist designing an air traffic control model, and you choose to leverage Oracle AutoML. You understand that the Oracle AutoML pipeline consists of multiple stages and automatically operates in a certain sequence. What is the correct sequence for the Oracle AutoML pipeline?

• A.Algorithm selection, Feature selection, Adaptive sampling, Hyperparameter tuning
• B.Adaptive sampling, Algorithm selection, Feature selection, Hyperparameter tuning
• C.Adaptive sampling, Feature selection, Algorithm selection, Hyperparameter tuning
• D.Algorithm selection, Adaptive sampling, Feature selection, Hyperparameter tuning

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Which of these options allow the sharing and loading back of ML models into a notebook session?

• A.Model provenance
• B.Model taxonomy
• C.Model deployment
• D.Model catalog

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You have received machine learning model training code, without clear information about the optimal shape to run the training on. How would you proceed to identify the optimal compute shape for your model training that provides a balanced cost and processing time?

• A.Start with a smaller shape and monitor the job run metrics and time required to complete the model training. If the compute shape is not fully utilized, tune the model parameters, and rerun the job. Repeat the process until the shape resources are fully utilized.
• B.Start with the strongest compute shape Jobs support and monitor the job run metrics and time required to complete the model training. Tune the model so that it utilizes as much compute resources as possible, even at an increased cost.
• C.Start with a small shape and monitor the utilization metrics and time required to complete the model training. If the compute shape is fully utilized, change to compute that has more resources and rerun the job. Repeat the process until the processing time does not improve.
• D.Start with a random compute shape and monitor the utilization metrics and time required to finish the model training. Perform model training optimization and performance tests in advance to identify the right compute shape before running the model training as a job.

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You are working as a data scientist for a healthcare company. They decided to analyze the data to find patterns in a large volume of electronic medical records. You are asked to build a PySpark solution to analyze these records in a JupyterLab notebook. What is the order of recommended steps to develop a PySpark application in OCI Data Science?

• A.Launch a notebook session, configure core-site.xml, install a PySpark conda environment, develop your PySpark application, create a Data Flow application with the Accelerated Data Science (ADS) SDK
• B.Configure core-site.xml, install a PySpark conda environment, create a Data Flow application with the Accelerated Data Science (ADS) SDK, develop your PySpark application, launch a notebook session
• C.Install a Spark conda environment, configure core-site.xml, launch a notebook session, create a Data Flow application with the Accelerated Data Science (ADS) SDK, develop your PySpark application
• D.Launch a notebook session, install a PySpark conda environment, configure core-site.xml, develop your PySpark application, create a Data Flow application with the Accelerated Data Science (ADS) SDK

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While working with Git on Oracle Cloud Infrastructure (OCI) Data Science, you notice that two of the operations are taking more time than the others due to your slow internet speed. Which TWO operations would experience the delay?

• A.Moving the changes into staging area for the next commit
• B.Updating the local repo to match the content from a remote repository
• C.Pushing changes to a remote repository
• D.Making a commit that is taking a snapshot of the local repository for the next push
• E.Converting an existing local project folder to a Git repository

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