100% PASS RATE Oracle Cloud 1z0-1110-23 Certified Exam DUMP with 80 Questions
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NEW QUESTION # 15
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 is high.
- B. Model 1, because the test accuracy is high.
- C. Model 2, because recall has more impact on predictions in this use se.
- D. Model 1, because recall has lesser impact on predictions in this use case
Answer: C
NEW QUESTION # 16
data scientist, you use the Oracle Cloud Infrastructure (OCI) Language service to train custom models. Which types of custom models can be trained?
- A. Sentiment Analysis, Named Entity Recognition (NER)
- B. Object detection, Text classification
- C. Image classification, Named Entity Recognition (NER)
- D. Text classification, Named Entity Recognition (NER)
Answer: D
NEW QUESTION # 17
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()
Answer: B
NEW QUESTION # 18
. 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 fewer instances.
- B. Update the deployment to use a larger virtual machine (more CPUs/memory).
- C. Update the deployment to add more instances.
- D. Delete the deployment.
- E. Reduce the load balancer bandwidth limit so that fewer requests come in.
Answer: B,C,E
NEW QUESTION # 19
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 is used to disable the reporting of false alarms.
- C. It changes the sensitivity of the model to detecting anomalies.
- D. It determines how many false alarms occur before an error message is generated.
Answer: C
NEW QUESTION # 20
Which of the following TWO non-open source JupyterLab extensions has Oracle Cloud In-frastructure (OCI) Data Science developed and added to the notebook session experience?
- A. Terminal
- B. Table of Contents
- C. Notebook Examples
- D. Environment Explorer
- E. Command Palette
Answer: C,D
NEW QUESTION # 21
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{}
Answer: C
NEW QUESTION # 22
You have just completed analyzing a set of images by using Oracle Cloud Infrastructure (OCI) Data Labelling, and you want to export the annotated data. Which two formats are supported?
- A. CONLL V2003
- B. Spacy
- C. COCO
- D. Data Labelling Service Proprietary JSON
Answer: B,C
NEW QUESTION # 23
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 fewer instances.
- B. Update the deployment to use a larger virtual machine (mare CPUs/memory).
- C. Update the deployment to add more instances.
- D. Reduce the load balancer bandwidth limit so that fewer requests come in.
- E. Delete the deployment.
Answer: C
NEW QUESTION # 24
Which two statements are true about published conda environments?
- A. They are curated by Oracle Cloud Infrastructure (OCI) Data Science.
- B. The odac conda init command is used to configure the location of published conda environments.
- C. You can only create a published conda environment by modifying a Data Science conda environment.
- D. Your notebook session acts as the source to share published conda environments with team members.
- E. In addition to service job run environment variables, conda environment variables can be used in Data Science Jobs.
Answer: D,E
NEW QUESTION # 25
What preparation steps are required to access an Oracle AI service SDK from a Data Science notebook session?
- A. Create and upload the APIsigning key and config file.
- B. Create and upload score.py and runtime.yaml.
- C. Call the ADS command to enable AI integration
- D. Import the REST API.
Answer: A
NEW QUESTION # 26
You are working as a data scientist for a healthcare company. They decide to analyze the data to find patterns in a large volume of electronic medical records. You are asked to build a PySpark solution to analyze these records in a JupyterLab notebook. What is the order of recommended steps to develop a PySpark application in Oracle Cloud Infrastructure (OCI) Data Science?
- A. Launch a notebook session. Configure core-site.xml. Install a PySpark conda environment.
- B. Develop your PySpark application. Create a Data Flow application with the Accelerated Data Science (ADS) SDK.
- C. Launch a notebook session. Install a PySpark conda environment. Configure core-site.xml.
Develop your PySpark application. Create a Data Flow application with the Accelerated Data Science (ADS) SDK. - D. Configure core-site.xml. Install a PySpark conda environment. Create a Data Flow application with the Accelerated Data Science (ADS) SDK. Develop your PySpark application. Launch a notebook session.
- E. Install a Spark conda environment. Configure core-site.xml. Launch a notebook session.
Create a Data Flow application with the Accelerated Data Science (ADS) SDK. Develop your PySpark application.
Answer: C
NEW QUESTION # 27
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. Download all your files and data to your local machine, delete your notebook session, provision a new notebook session on a larger compute shape, and upload your files from your local machine to the new notebook session.
- B. 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 session with a larger compute shape selected. - C. Create a temporary bucket on Object Storage, write all your files and data to Object Storage, delete your notebook session, provision a new notebook session on a larger compute shape, Want any exam dump in pdf email me at [email protected] (Little Paid) and copy your files and data from your temporary bucket onto your new notebook session.
- D. Deactivate your notebook session, provision a new notebook session on a larger compute shape and re-create all of your file changes.
Answer: B
NEW QUESTION # 28
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. Adaptive Sampling
- B. Feature Selection
- C. Feature Extraction
- D. Model Deployment
- E. Algorithm Selection
Answer: A,B,D
NEW QUESTION # 29
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. OCI Console
- B. Mobile App
- C. Programming Language Software Development Kit (SDK)
- D. Command Line Interface (CLI)
Answer: C
NEW QUESTION # 30
You are a data scientist building a pipeline in the Oracle Cloud Infrastructure (OCI) Data Science service for your machine learning project. You want to optimize the pipeline completion time by running some steps in parallel. Which statement is true about running pipeline steps in parallel?
- A. Pipeline steps can be run in sequence or in parallel, as long as they create a directed acyclic graph (DAG).
- B. Steps in a pipeline can be run only sequentially.
- C. All pipeline steps are always run in parallel.
- D. Parallel steps cannot be run if they are completely independent of each other.
Answer: A
NEW QUESTION # 31
You are creating an Oracle Cloud Infrastructure (OCI) Data Science job that will run on a recurring basis in a production environment. This job will pick up sensitive data from an Object Storage bucket, train a model, and save it to the model catalog.
How would you design the authentication mechanism for the job?
- A. Create a pre-authenticated request (PAR) for the Object Storage bucket, and use that in the job code.
- B. Use the resource principal of the job run as the signer in the job code, ensuring there is a dynamic group for this job run with appropriate access to Object Storage and the model catalog.
- C. Package your personal OCI config file and keys in the job artifact
- D. Store your personal OCI config file and keys in the Vault and access the Vault through the job run resource principal.
Answer: B
NEW QUESTION # 32
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. Execute the inference logic code.
- C. Define the inference server dependencies
- D. Configure the deployment infrastructure.
Answer: B
NEW QUESTION # 33
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. Local Interpretable Model-Agnostic Explanations
- B. Feature Dependence Explanations
- C. Accumulated Local Effects
- D. Feature Permutation Importance Explanations
Answer: C
NEW QUESTION # 34
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