Prepare for the Oracle Cloud Infrastructure Data Science 2023 Professional exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.
QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Oracle 1Z0-1110-23 exam and achieve success.
Six months ago, you created and deployed a model that predicts customer churn for a call
centre. Initially, it was yielding quality predictions. However, over the last two months, users are
questioning the credibility of the predictions.
Which two methods would you employ to verify the accuracy of the model?
You want to write a program that performs document analysis tasks such as extracting text and
tables from a document. Which Oracle AI service would you use?
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?
As a data scientist, you create models for cancer prediction based on mammographic images.
The correct identification is very crucial in this case. After evaluating two models, you arrive at the
following confusion matrix.
Model 1 has Test accuracy is 80% and recall is 70%.
* Model 2 has Test accuracy is 75% and recall is 85%.
Which model would you prefer and why?
In the Oracle Cloud Infrastructure (OCI) Data Science service, how does Model Catalog help with
model deployment and management in MLOps?
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