Oracle Cloud Infrastructure Data Science 2022 Professional Valid Exam Format & 1z0-1110-22 Latest Practice Questions & Oracle Cloud Infrastructure Data Science 2022 Professional Free Updated Training

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Oracle Cloud Infrastructure Data Science 2022 Professional Sample Questions (Q53-Q58):

NEW QUESTION # 53
You have created a conda environment in your notebook session. This is the first time you are working with published conda environments. You have also created an Object Storage bucket with permission to manage the bucket Which TWO commands are required to publish the conda environment?

  • A. odsc conda create –file manifest.yaml
  • B. odsc conda init -b <your-bucket-name> -a <api_key or resource_principal>
  • C. odsc conda list –override
  • D. odsc conda publish –slug <SLUG>

Answer: B,D

NEW QUESTION # 54
You are a data scientist trying to load data into your notebook session. You understand that Accelerated Data Science (ADS) SDK supports loading various data formats. Which of the following THREE are ADS supported data formats?

  • A. XML
  • B. Pandas DataFram
  • C. JSON
  • D. Raw Images
  • E. DOCX

Answer: A,B,C

NEW QUESTION # 55
You want to make your model more parsimonious to reduce the cost of collecting and processing dat a. You plan to do this by removing features that are highly correlated. You would like to create a heat map that displays the correlation so that you can identify candidate features to remove. Which Accelerated Data Science (ADS) SDK method would be appropriate to display the correlation between Continuous and Categorical features?

  • A. Correlation_ratio_plot{}
  • B. Pearson_plot{}
  • C. Corr{}
  • D. Cramersv_plot{}

Answer: A

NEW QUESTION # 56
Which feature of the Oracle Cloud Infrastructure (OCI) Vision service helps you generate in-dexing tags for a collection of marketing photographs?

  • A. Image classification
  • B. Text recognition
  • C. Key Value extraction
  • D. Document classification

Answer: B

NEW QUESTION # 57
Six months ago, you created and deployed a model that predicts customer churn for a call center. Initially, it was yielding quality predictions. However, over the last two months, users have been questioning the credibility of the predictions. Which TWO methods customer churn would you employ to verify the accuracy of the model?

  • A. Operational monitoring
  • B. Redeploy the model
  • C. Validate the model using recent data
  • D. Drift monitoring
  • E. Retrain the model

Answer: C,E

NEW QUESTION # 58
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