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Oracle Mock 1z0-1110-22 Exam

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The Oracle 1z0-1110-22 exam is a certification exam designed for professionals who want to demonstrate their expertise in Oracle Cloud Infrastructure data science. This exam is intended to validate the knowledge and skills required to design, implement, and manage data science solutions using Oracle Cloud Infrastructure Data Science. Passing this exam will prove that you have the necessary skills to enable machine learning models and analyze big data.

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Latest Updated Oracle Mock 1z0-1110-22 Exam: Oracle Cloud Infrastructure Data Science 2022 Professional & Reliable 1z0-1110-22 Exam Pattern

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The exam covers a wide range of topics, from data preparation and cleaning to machine learning and predictive analytics. It also tests the candidate’s knowledge of cloud infrastructure and the ability to deploy and manage data science models in a cloud environment. The exam is designed to measure the candidate’s ability to work with large datasets and extract insights using advanced analytics techniques.

To prepare for the Oracle 1z0-1110-22 exam, candidates should have a strong understanding of machine learning concepts, algorithms, and tools. They should also have experience using Python programming language and working with data in various formats. Oracle offers training courses and certification preparation resources to help candidates prepare for the exam. Upon passing the exam, candidates will earn the Oracle Cloud Infrastructure Data Science 2022 Professional certification, which demonstrates their mastery of machine learning techniques and their ability to use Oracle Cloud Infrastructure Data Science to build and deploy machine learning models.

Oracle Cloud Infrastructure Data Science 2022 Professional Sample Questions (Q56-Q61):

NEW QUESTION # 56
You have trained three different models on your data set using Oracle AutoML. You want to visualize the behavior of each of the models, including the baseline model, on the test set. Which class should be used from the Accelerated Data Science (ADS) SDK to visually compare the models?

  • A. ADSTuner
  • B. ADS Evaluator
  • C. EvaluationMetrics
  • D. ADS Explainer

Answer: C

NEW QUESTION # 57
During a job run, you receive an error message that no space is left on your disk device. To solve the problem, you must increase the size of the job storage. What would be the most effi-cient way to do this with Data Science Jobs?

  • A. Your code using too much disk space. Refactor the code to identify the problem.
  • B. Create a new job with increased storage size and then run the job.
  • C. Edit the job, change the size of the storage of your job, and start a new job run.
  • D. On the job run, set the environment variable that helps increase the size of the storage.

Answer: C

NEW QUESTION # 58
Select two reasons why it is important to rotate encryption keys when using Oracle Cloud In-frastructure (OCI) Vault to store credentials or other secrets.?

  • A. Key rotation reduces risk if a key is ever compromised.
  • B. Key rotation improves encryption efficiency.
  • C. Periodically rotating keys limits the amount of data encrypted by one key version.
  • D. Key rotation allows you to encrypt no more than five keys at a time.
  • E. Periodically rotating keys make it easier to reuse key.

Answer: A,E

NEW QUESTION # 59
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 random compute shape and monitor the utilization metrics and time required to finish the model training Perform model training optimizations and performance tests in advance to identify the right compute shape before running the model training as a job.
  • B. Start with a smaller 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 re-run the job. Repeat the process until the processing time does not improve.
  • C. 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.
  • D. Start with the strangest 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.

Answer: B

NEW QUESTION # 60
While reviewing your data, you discover that your data set has a class imbalance. You are aware that the Accelerated Data Science (ADS) SDK provides multiple built-in automatic transformation tools for data set transformation. Which would be the right tool to correct any imbalance between the classes?

  • A. suggeste_recoomendations()
  • B. visualize_transforms()
  • C. sample()
  • D. auto_transform()

Answer: D

NEW QUESTION # 61
……

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