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NEW QUESTION # 28
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. Sentence diagramming
- B. Punctuation correction
- C. Table extraction
- D. Topic classification
- E. Sentiment analysis
Answer: D
NEW QUESTION # 29
You are a data scientist working inside a notebook session and you attempt to pip install a package from a public repository that is not included in your conda environment. After running this command, you get a network timeout error.
What might be missing from your networking configuration?
- A. NAT Gateway with public internet access.
- B. Primary Virtual Network Interface Card (VNIC).
- C. Service Gateway with private subnet access
- D. FastConnect to an on-premises network.
Answer: A
NEW QUESTION # 30
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. Configure a block volume.
- B. Use command-line variables.
- C. Use environmental variables
- D. Configure a compute shape.
Answer: C
NEW QUESTION # 31
You are a data scientist leveraging Oracle Cloud Infrastructure (OCI) Data Science to create a model and need some additional Python libraries for processing genome sequencing data. Which of the following THREE statements are correct with respect to installing additional Python libraries to process the data?
- A. You can only install libraries using yum and pip as a normal user.
- B. You cannot install a library that's not preinstalled in the provided image
- C. OCI Data Science allows root privileges in notebook sessions.
- D. You can install private or custom libraries from your own internal repositories.
- E. You can install any open source package available on a publicly accessible Python Package Index (PyPI) repository.
Answer: A,C,E
NEW QUESTION # 32
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. Update the deployment to use a larger virtual machine (mare CPUs/memory).
- B. Update the deployment to add more instances.
- C. Delete the deployment.
- D. Update the deployment to use fewer instances.
- E. Reduce the load balancer bandwidth limit so that fewer requests come in.
Answer: B
NEW QUESTION # 33
As a data scientist, you have stored sensitive data in a database. You need to protect this data by using a master encryption algorithm, which uses symmetric keys. Which master encryption algorithm would you choose in the Oracle Cloud Infrastructure (OCI) Vault service?
- A. Rivert-Shamir-Adleman Keys
- B. Elliptical Curve Cryptography Digital Signature Algorithm
- C. Triple Data Encryption Standard Algorithm
- D. Advanced Encryption Standard Keys
Answer: D
NEW QUESTION # 34
You are building a model and need input that represents data as morning, afternoon, or evening. However, the data contains a time stamp. What part of the Data Science life cycle would you be in when creating the new variable?
- A. Model type selection
- B. Feature engineering
- C. Data access
- D. Model validation
Answer: D
NEW QUESTION # 35
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 1, because recall has lesser impact on predictions in this use case
- B. Model 2, because recall is high.
- C. Model 2, because recall has more impact on predictions in this use se.
- D. Model 1, because the test accuracy is high.
Answer: C
NEW QUESTION # 36
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. Show_corr{}
- B. Compute{}
- C. To_xgb{}
- D. Show_in_notebook{}
Answer: D
NEW QUESTION # 37
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 using object detection, by drawing bounding boxes to an im-age.
- B. Adding a single label to an image.
- C. Adding multiple labels to an image.
- D. Adding labels to image using semantic segmentation, by drawing multiple bounding boxes to an image.
- E. Adding labels to an image by drawing bounding box to an image, is not supported by Data Labeling
Answer: A,B,C
NEW QUESTION # 38
You are asked to prepare data for a custom-built model that requires transcribing Spanish video recordings into a readable text format with profane words identified.
Which Oracle Cloud service would you use?
- A. OCI Speech
- B. OCI Anomaly Detection
- C. OCI Translation
- D. OCI Language
Answer: A
NEW QUESTION # 39
3. When preparing your model artifact to save it to the Oracle Cloud Infrastructure (OCI) Data Science model catalog, you create a score.py file. What is the purpose of the score.py file?
- A. Define the compute scaling strategy.
- B. Define the inference server dependencies
- C. Configure the deployment infrastructure.
- D. Execute the inference logic code.
Answer: D
NEW QUESTION # 40
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. Object Detection
- B. Key-Point and Landmark
- C. Classification (single/multi label)
- D. Named Entity Extraction
- E. Polygonal Segmentation
- F. Semantic Segmentation
Answer: A,C,D
NEW QUESTION # 41
Which TWO statements are true about published conda environments?
- A. They can be used in Data Science Jobs and model deployments.
- B. The odsc conda init command is used to configure the location of published conda en-vironments.
- C. You can only create published conda environment by modifying a Data Science conde
- D. Your notebook session acts as the source to share published conda environment with team members.
- E. They are curated by Oracle Cloud Infrastructure (OCI) Data Science.
Answer: B,D
NEW QUESTION # 42
In the Oracle Cloud Infrastructure (OCI) Data Science service, how does Model Catalog help with model deployment and management in MLOps?
- A. It provides a centralized and scalable way to manage models and their metadata.
- B. It is a database that stores all the features used in a machine learning model.
- C. It helps to automate the feature engineering process.
- D. It helps to package the model and its dependencies into a lightweight, portable container.
Answer: A
NEW QUESTION # 43
You want to write a Python script to create a collection of different projects for your data science team. Which Oracle Cloud Infrastructure (OCI) Data Science interface would you use?
- A. Mobile App
- B. The OCI Software Development Kit (SDK)
- C. Command line interface (CLI)
- D. OCI Console
Answer: B
NEW QUESTION # 44
You want to evaluate the relationship between feature values and target variables. You have a large number of observations having a near uniform distribution and the features are highly correlated.
Which model explanation technique should you choose?
- A. Feature Permutation Importance Explanations
- B. Accumulated Local Effects
- C. Feature Dependence Explanations
- D. Local Interpretable Model-Agnostic Explanations
Answer: B
NEW QUESTION # 45
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. ADSEvaluator
- C. EvaluationMetrics
- D. ADSExplainer
Answer: B
NEW QUESTION # 46
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. Drift monitoring
- D. Retrain the model
- E. Validate the model using recent data
Answer: D,E
NEW QUESTION # 47
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. Edit the job, change the size of the storage of your job, and start a new job run.
- B. Create a new job with increased storage size and then run the job.
- C. On the job run, set the environment variable that helps increase the size of the storage.
- D. Your code using too much disk space. Refactor the code to identify the problem.
Answer: A
NEW QUESTION # 48
You want to make your model more parsimonious 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 would be appropriate to display the correlation between Continuous and Categorical features?
- A. Pearson_plot{}
- B. Corr{}
- C. Cramersv_plot{}
- D. Correlation_ratio_plot{}
Answer: D
NEW QUESTION # 49
As you are working in your notebook session, you find that your notebook session does not have enough compute CPU and memory for your workload. How would you scale up your notebook session without losing your work?
- A. Ensure your files and environments are written to the block volume storage under the /home/datascience directory, deactivate the notebook session, and activate the notebook larger compute shape selected.
- B. Create a temporary bucket in Object Storage, write all your files and data to Object Storage, delete tur ctebook session, provision a new notebook session on a larger compute shape, and capy your flies and data from your temporary bucket onto your new notebook session.
- C. Deactivate your notebook session, provision a new notebook session on larger compute shape, and re-create all your file changes.
- D. Down your files and data to your local machine, delete your notebook session, provision tebook session on a larger compute shape, and upload your files from your local the new notebook session.
Answer: A
NEW QUESTION # 50
You are using Oracle Cloud Infrastructure (OCI) Anomaly Detection to train a model to detect anomalies in pump sensor data. How does the required False Alarm Probability setting affect an anomaly detection model?
- A. It adds a score to each signal indicating the probability that its a false alarm.
- B. It changes the sensitivity of the model to detecting anomalies.
- C. It determines how many false alarms occur before an error message is generated.
- D. It is used to disable the reporting of false alarms.
Answer: B
NEW QUESTION # 51
As a data scientist, you are tasked with creating a model training job that is expected to take different hyperparameter values on every run. What is the most efficient way to set those parameters with Oracle Data Science Jobs?
- A. Create your code to expect different parameters as command line arguments and create a new job every time you run the code.
- B. Create a new job by setting the required parameters in your code and create a new job for every code change.
- C. Create your code to expect different parameters either as environment variables or as command line arguments, which are set on every job run with different values.
- D. Create a new job every time you need to run your code and pass the parameters as environment variables.
Answer: C
NEW QUESTION # 52
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