2023年最新のの問題Oracle Cloudと1z0-1110-23リアル試験問をマスターせよ！
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Oracle 1z0-1110-23 認定試験の出題範囲：
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質問 # 10
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. Edit the job, change the size of the storage of your job, and start a new job run.
- C. On the job run, set the environment variable that helps increase the size of the storage.
- D. Create a new job with increased storage size and then run the job.
正解：B
質問 # 11
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. Raw Images
- C. DOCX
- D. JSON
- E. Pandas DataFrame
正解：A、E
質問 # 12
You are a computer vision engineer building an image recognition model. You decide to use Oracle Data Labeling to annotate your image data. Which of the following THREE are possible ways to annotate an image in Data Labeling?
- A. Adding labels to an image by drawing bounding box to an image, is not supported by Data Labeling
- B. Adding labels to image using semantic segmentation, by drawing multiple bounding boxes to an image.
- C. Adding labels to an image using object detection, by drawing bounding boxes to an im-age.
- D. Adding a single label to an image.
- E. Adding multiple labels to an image.
正解：C、D、E
質問 # 13
You have just received a new data set from a colleague. You want to quickly find out summary information about the data set, such as the types of features, total number of observations, and data distributions, Which Accelerated Data Science (ADS) SDK method from the AD&Dataset class would you use?
- A. To_xgb{}
- B. Show_corr{}
- C. Show_in_notebook{}
- D. Compute{}
正解：C
質問 # 14
As a data scientist, you are trying to automate a machine learning (ML) workflow and have decided to use Oracle Cloud Infrastructure (OCI) AutoML Pipeline.
Which three are part of the AutoML Pipeline?
- A. Feature Extraction
- B. Feature Selection
- C. Adaptive Sampling
- D. Algorithm Selection
- E. Model Deployment
正解：B、C、E
質問 # 15
You have created a Data Science project in a compartment called Development and shared it with a group of collaborators. You now need to move the project to a different compartment called Production after completing the current development iteration.
Which statement is correct?
- A. Moving a project to a different compartment also moves its associated notebook sessions and models to the new compartment.
- B. You cannot move a project to a different compartment after it has been created.
- C. You can move a project to a different compartment without affecting its associated notebook sessions and models
- D. Moving a project to a different compartment requires deleting all its associated notebook sessions and models first.
正解：A
質問 # 16
You want to make your model more frugal to reduce the cost of collecting and processing data.
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 is appropriate to display the comparability between Continuous and Categorical features?
- A. cramersv_plot()
- B. correlation_ratio_plot()
- C. pearson_plot()
- D. corr()
正解：B
質問 # 17
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. EvaluationMetrics
- B. ADSTuner
- C. ADSEvaluator
- D. ADSExplainer
正解：C
質問 # 18
In the Oracle Cloud Infrastructure (OCI) Data Science service, how does Model Catalog help with model deployment and management in MLOps?
- A. It is a database that stores all the features used in a machine learning model.
- B. It helps to automate the feature engineering process.
- C. It helps to package the model and its dependencies into a lightweight, portable container.
- D. It provides a centralized and scalable way to manage models and their metadata.
正解：D
質問 # 19
The Accelerated Data Science (ADS) model evaluation classes support different types of machine learning modeling techniques. Which three types of modeling techniques are supported by ADS Evaluators?
- A. Binary Classification
- B. K-means Clustering
- C. Recurrent Neural Network
- D. Regression Analysis
- E. Multiclass Classification
- F. Principal Component Analysis
正解：A、D、E
質問 # 20
You are a data scientist with a set of text and image files that need annotation, and you want to use Oracle Cloud Infrastructure (OCI) Data Labeling. Which of the following THREE an-notation classes are supported by the tool.?
- A. Named Entity Extraction
- B. Key-Point and Landmark
- C. Classification (single/multi label)
- D. Polygonal Segmentation
- E. Semantic Segmentation
- F. Object Detection
正解：A、C、F
質問 # 21
You want to ensure that all stdout and stderr from your code are automatically collected and logged, without implementing additional logging in your code. How would you achieve this with Data Science Jobs?
- A. Make sure that your code is using the standard logging library and then store all the logs to Object Storage at the end of the job.
- B. Create your own log group and use a third-party logging service to capture job run details for log collection and storing.
- C. You can implement custom logging in your code by using the Data Science Jobs logging service.
- D. On job creation, enable logging and select a log group. Then, select either a log or the option to enable automatic log creation.
正解：D
質問 # 22
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 Want any exam dump in pdf email me at [email protected] (Little Paid)
- B. Algorithm selection, Adaptive sampling, Feature selection, Hyperparameter tuning
- C. Adaptive sampling, Feature selection, Algorithm selection, Hyperparameter tuning
- D. Adaptive sampling, Algorithm selection, Feature selection, Hyperparameter tuning
正解：D
質問 # 23
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?
- A. Model 2, because recall has more impact on predictions in this use se.
- B. Model 1, because recall has lesser impact on predictions in this use case
- C. Model 2, because recall is high.
- D. Model 1, because the test accuracy is high.
正解：A
質問 # 24
You are attempting to save a model from a notebook session to the model catalog by using the Accelerated Data Science (ADS) SDK, with resource principal as the authentication signer, and you get a 404 authentication error. Which two should you look for to ensure permissions are set up correctly?
- A. The model artifact is saved to the block volume of the notebook session.
- B. The networking configuration allows access to Oracle Cloud Infrastructure services through a Service Gateway.
- C. The policy for your user group grants manages permissions for the model catalog in this compartment.
- D. The policy for a dynamic group grant manages permissions for the model catalog in it compartment.
- E. A dynamic group has rules that matching the notebook sessions in it compartment.
正解：C、E
質問 # 25
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. 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.
- B. Rewrite your code so that it is a single executable Python or Bash/Shell script file.
- C. ZIP the entire code project folder and upload it as a Job artifact on job creation. Jobs identifies the main executable file automatically.
- D. 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.
正解：A
質問 # 26
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