1z0-1110-22 Free Certification Exam Material from PracticeMaterial with 58 Questions [Q15-Q35]

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1z0-1110-22 Free Certification Exam Material from PracticeMaterial with 58 Questions

Use Real 1z0-1110-22 – 100% Cover Real Exam Questions

The Oracle 1z0-1110-22 certification is a valuable asset for data scientists who want to demonstrate their proficiency in using Oracle Cloud Infrastructure for data science projects. This certification is recognized globally and is highly sought after by employers in the IT industry. By obtaining this certification, data scientists can enhance their career prospects and increase their earning potential.

Q15. You want to evaluate the relationship between feature values and model predictions. You sus-pect that some of the features are correlated. Which model explanation technique would you recommend?

Accumulated Local Effects.

Local Interpretable Model-Agnostic Explanations.

Feature Dependence Explanations.

Feature Permutation Importance Explanations.

Q16. You are a data scientist working for a utilities company. You have developed an algorith that detects anomalies from a utility reader in the grid. The size of the model artifact is about 2 GB, and you are trying to store it in the model catalog. Which THREE interfaces would you use to save the model artifact into the model catalog?

Console

Accelerated Data Science (ADS) Software Development Kit (SDK)

Oracle Cloud Infrastructure (OCI) Command Line Interface (CLI)

OCI Python SDK

Git CLI

ODSC CLI

Q17. 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.?

Object Detection

Named Entity Extraction

Classification (single/multi label)

Key-Point and Landmark

Polygonal Segmentation

Semantic Segmentation

Q18. For your next data science project, you need access to public geospatial images. Which Oracle Cloud service provides free access to those images?

Oracle Big Data Service

Oracle Analytics Claud

Oracle Cloud Infrastructure (OCI) Data Science

Oracle Open Data

Q19. 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?

OCI Translation

OCI Language

OCI Anomaly Detection

OCI Speech

Q20. 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 pa-rameters with Oracle Data Science Jobs?

Create a new job every time you need to run your code and pass the parameters as en-vironment variables.

Create your code to expect different parameters as command line arguments, and create it new job every time you run the code.

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.

Create a new no by setting the required parameters in your code, and create a new job for mery code change.

Q21. 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?

odsc conda publish –slug <SLUG>

odsc conda create –file manifest.yaml

odsc conda init -b <your-bucket-name> -a <api_key or resource_principal>

odsc conda list –override

Q22. You have built a machine model to predict whether a bank customer is going to default on a loan. You want to use Local Interpretable Model-Agnostic Explanations (LIME) to understand a specific prediction. What is the key idea behind LIME?

Model-agnostic techniques are more interpretable than techniques that are dependent on the types of models.

Local explanation techniques are model agnostic, while global explanation techniques are not.

Global behavior of a machine learning model may be complex, while the local behavior may be approximated with a simpler surrogate model.

Global and local behaviors of machine learning models are similar.

Q23. 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?

Model type selection

Model validation

Data access

Feature engineering

Q24. 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?

Environment Explorer

Table of Contents

Command Palette

Notebook Examples

Terminal

Q25. You are a computer vision engineer building an image recognition model. You decide to use Oracle Data Labeling to annotate your image dat a. Which of the following THREE are possible ways to annotate an image in Data Labeling?

Adding labels to image using semantic segmentation, by drawing multiple bounding boxes to an image.

Adding a single label to an image.

Adding labels to an image by drawing bounding box to an image, is not supported by Data Labeling

Adding labels to an image using object detection, by drawing bounding boxes to an im-age.

Adding multiple labels to an image.

Q26. Which feature of the Oracle Cloud Infrastructure (OCI) Vision service helps you generate in-dexing tags for a collection of marketing photographs?

Document classification

Image classification

Text recognition

Key Value extraction

Q27. 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?

Table extraction

Punctuation correction

Sentence diagramming

Topic classification

Sentiment analysis

Q28. After you have created and opened a notebook session, you want to use the Accelerated Data Science (ADS) SDK to access your data and get started with exploratory data analysis. From which TWO places can you access the ADS SDK?

Oracle Autonomous Data Warehouse

Oracle Machine Learning

Conda environments in Oracle Cloud infrastructure (OCI) Data Science.

Python Package Index (PyPi)

Oracle Big Data Service

Q29. As a data scientist, you are working on a global health data set that has data from more than 50 countries. You want to encode three features, such as ‘countries’, ‘race’, and ‘body organ’ as categories. Which option would you use to encode the categorical feature?

DataFramLabelEncode()

auto_transform()

OneHotEncoder()

show_in_notebook()

Q30. While reviewing your data, you discover that your data set has a class imbalance. You are aware that the Accelerated Data Science (ADS) SDK provides multiple built-in automatic transformation tools for data set transformation. Which would be the right tool to correct any imbalance between the classes?

sample()

suggeste_recoomendations()

auto_transform()

visualize_transforms()

Q31. You are a data scientist working for a manufacturing company, you have developed a fore-casting model to predict the sales demand in the upcoming months. You created a model artifact that contained custom logic requiring third party libraries. When you deployed the model, it failed to run because you did not include all the third-party dependencies in the model artifact.?

Score.py

Requirement.txt

Model_artifact_validate.py

Runtime.yaml

Q32. You have an embarrassingly parallel or distributed batch job on a large amount of data running using Data Science Jobs What would be the best approach to run the workload?

Create the job in Data Science Jobs and then start the number of simultaneous job runs required for your workload.

Create the job in Data Science Jobs and start a job run. When it is done, start a new job run until you achieve the number of runs required.

Reconfigure the job run because Data science jobs does not support embarrassingly parallel.

Create a new job for every job run that you have to run in parallel, because the Date Science Jobs service can have only one job run per job.

Q33. 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?

On the job run, set the environment variable that helps increase the size of the storage.

Your code using too much disk space. Refactor the code to identify the problem.

Edit the job, change the size of the storage of your job, and start a new job run.

Create a new job with increased storage size and then run the job.

Q34. 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?

The networking configuration allows access to the Oracle Cloud Infrastructure (OCI) services through a Service Gateway.

The model artifact is saved to the block volume of the notebook session.

The dynamic group’s matching rule exists for notebook sessions in this compartment.

The policy for the dynamic group grants manages permissions for the model catalog in this compartment.

The policy for your user group grants manage permissions for the model catalog in this compartment.

Q35. You have a data set with fewer than 1000 observations, and you are using Oracle AutoML to build a classifier. While visualizing the results of each stage of the Oracle AutoML pipeline, you notice that no visualization has been generated for one of the stages. Which stage is not visualized?

Feature selection

Algorithm selection

Adaptive sampling

Hyperparameter tuning

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The Oracle 1z0-1110-22 exam covers a wide range of topics related to data science, including data preparation, machine learning, model deployment, data visualization, and data analysis. The exam is designed to test the candidate’s knowledge and skills in these areas, as well as their ability to apply them in real-world scenarios. The exam consists of 60 multiple-choice questions and must be completed within 105 minutes.

The Oracle 1z0-1110-22 certification exam is designed for professionals who are interested in validating their skills in deploying and managing data science projects on Oracle Cloud Infrastructure. This certification exam tests the knowledge and skills required to design, develop, and deploy data science projects on Oracle Cloud Infrastructure. Candidates who pass the exam will earn the Oracle Cloud Infrastructure Data Science 2022 Professional certification.

Dumps Brief Outline Of The 1z0-1110-22 Exam: https://www.practicematerial.com/1z0-1110-22-exam-materials.html

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