Free Oracle 1z0-1110-23 Exam Dumps Questions & Answers

You are a data scientist leveraging the Oracle Cloud Infrastructure (OCI) Language AI service for various types of text analyses. Which TWO capabilities can you utilize with this tool?

• A.  Punctuation correction
• B.  Sentence diagramming
• C.  Table extraction
• D.  Sentiment analysis
• E.  Topic classification

You have an embarrassingly parallel or distributed batch job on a large amount of data that you consider running using Data Science Jobs. What would be the best approach to run the workload?

• A.  Reconfigure the job run because Data Science Jobs does not support embarrassingly parallel workloads.
• B.  Create the job in Data Science Jobs and start a job run. When it is done, start a new job run until you achieve the number of runs required.
• C.  Create the job in Data Science Jobs and then start the number of simultaneous jobs runs required for your workload.
• D.  Create a new job for every job run that you have to run in parallel, because the Data Science Jobs service can have only one job run per job.

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 subfolders and classes.
What is the best way to run this project as a Job?

• A.  Rewrite your code so that it is a single executable Python or Bash/Shell script file.
• B.  ZIP the entire code project folder and upload it as a Job artifact. Jobs automatically identifies the_main_ top level where the code is run.
• C.  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.
• D.  ZIP the entire code project folder and upload it as a Job artifact on job creation. Jobs identifies the main executable file automatically.

You want to build a multistep machine learning workflow by using the Oracle Cloud Infrastructure (OCI) Data Science Pipeline feature. How would you configure the conda environment to run a pipeline step?

• A.  Use environmental variables
• B.  Configure a block volume.
• C.  Use command-line variables.
• D.  Configure a compute shape.

You realize that your model deployment is about to reach its utilization limit. What would you do to avoid the issue before requests start to fail?

• A.  Delete the deployment.
• B.  Reduce the load balancer bandwidth limit so that fewer requests come in.
• C.  Update the deployment to add more instances.
• D.  Update the deployment to use a larger virtual machine (mare CPUs/memory).
• E.  Update the deployment to use fewer instances.