2024 New 1z0-1096-23 Dumps - Real Oracle Exam Questions
Dependable 1z0-1096-23 Exam Dumps to Become Oracle Certified
NEW QUESTION # 15
Which output formats are supported by the SET SQLFORMAT command? (Choose three.)
- A. TXT
- B. HTML
(Correct) - C. CSV
- D. JSON
Answer: C,D
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/output-formats-supported-set
NEW QUESTION # 16
You have created an Oracle Machine Learning notebook and want to share it with another collaborator.
However, you do not want to provide the ability to run or modify the notebook in your workspace. Which three options can be used to do this? (Choose three.)
- A. Share the notebook as a Shared Oracle Machine Learning Template
- B. Provide the user Developer permission to your workspace.
- C. Export the notebook and import it into the other user's project
- D. Provide the user Viewer permission to your workspace
Answer: A,C,D
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/collaborate-oracle-machine-l
NEW QUESTION # 17
You are creating a job that should run a notebook every hour. You want to make sure that the job does not run repeatedly if there are more than five consecutive failures to run the job. Which option should you set while creating the job?
- A. Maximum Failure Allowed
- B. Timeout in Minutes
- C. Maximum Number of Runs
- D. Minimum Failure Allowed
Answer: A
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/get-started-jobs.html#GUID-
NEW QUESTION # 18
Which statement is FALSE about Oracle Machine Learning (OML) Notebooks?
- A. You can share notebooks with Import/Export operations.
- B. You can set the output format in SQL paragraphs of a notebook.
- C. Within notebook paragraphs you can switch between data views of tables, pie charts, bar charts, line plots and scatter plots.
- D. When visualizing a 1 million row database data using the built-in Zeppelin visualizers, OML will by default display the results on the entire table.
Answer: D
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/get-started-oracle-machine-le Typical Workflow For Using Notebooks To begin with Oracle Machine Learning Notebooks, refer to the tasks listed in the table as a guide. TasksMore InformationAccess Oracle Machine Learning Note-booksAccess Oracle Machine LearningCreate workspacesCreate Projects and WorkspacesCreate projectsCreate Projects and WorkspacesCreate notebooksCreate a NotebookRun a Notebook with Python InterpreterRun a Notebook with Python InterpreterUse the ScratchpadUse the Scratchpad-Create jobs to schedule notebooksCreate Jobs to Schedule Notebook
NEW QUESTION # 19
Which step in the AutoML pipeline involves reducing the size of the large data set into a small-er data set that adequately represents the original?
- A. Algorithm Selection
- B. Hyperparameter Tuning
- C. Feature Selection
- D. Adaptive Sampling
- E. Model Selection
Answer: D
Explanation:
Explanation
https://oralytics.com/2021/03/15/oml4py-automl-an-example/
NEW QUESTION # 20
What are three key features of Oracle Machine Learning Notebooks? (Choose three.)
- A. They support SQL, PL/SQL, JavaScript, and PHP scripting languages.
- B. They support integration with Oracle Data Miner-ID
- C. They enable job scheduling of notebooks on a recurring schedule.
- D. They enable access to in database implementation of machine learning algorithms.
- E. They provide a collaborative notebook interface on Oracle Autonomous Database.
Answer: C,D,E
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/
NEW QUESTION # 21
Which two types of permissions allow you tables and run any script on an owner's account? (Choose two.)
- A. Developer
- B. Manager
- C. Viewer
- D. Guest
Answer: A,B
Explanation:
Explanation
Grant Workspace Permissions You can collaborate with other users in Oracle Machine Learning by granting permissions to access your workspace. Your workspace contains your projects and note-books. By granting different types of permissions such as Manager, Developer, and Viewer, you can allow another user to view your workspace and perform different tasks in your projects and note-books such as edit, create, update, delete, run, view notebooks and so on. For more information about the permission types, see About Workspace Permission Types. Caution: If you grant the per-mission type Manager or Developer, then the user can also drop tables, create tables, and run any scripts at any time on your account. The user with Viewer permission type can only view your note-books, and is not authorized to run or make any changes to your notebooks
NEW QUESTION # 22
Which type of machine learning algorithm is used to deal with noise in incoming data?
- A. Regression
- B. Clustering
- C. Dimensionality Reduction
- D. Classification
Answer: C
Explanation:
Explanation
https://blogs.oracle.com/machinelearning/post/using-svd-for-dimensionality-reduction
NEW QUESTION # 23
You are tasked with building a predictive model that can estimate the price of houses, based on attributes like number of rooms, square-footage (size), location, neighborhood attributes, year built among others. Which three algorithms can you use to produce such a model with Oracle Machine Learning? (Choose three.)
- A. Generalized Linear Model (Classification)
- B. Generalized Linear Model (Regression)
- C. Support Vector Machine (Regression)
- D. Explicit Semantic Analysis
- E. One-Class Support Vector Machine
- F. Neural Networks (Regression)
Answer: B,C,F
Explanation:
Explanation
https://learn.oracle.com/ols/course/using-oracle-machine-learning-with-autonomous-database/35644/98086/1493 This is from Oracle Course : Using Oracle Machine Learning with Autonomous Database Regression is a supervised learning technique used when the output attribute is a continuous numerical value, for example, the price of a property based on the attributes of the property and its locality, the humidity of an area, and so on.
Here is a list of all the algorithms offered by Oracle Machine Learning. Unsupervised learning does not involve direct control from the developer. In terms of defining an output attribute, the output attribute is a dependent attribute. And as there is no output attribute in unsupervised learning, there is no distinction between dependent and independent attributes.
NEW QUESTION # 24
When managing models using the Model Repository screen from the OML AutoML UI, what are the four operations a user can do to models and model deployments? (Choose four.)
- A. Change the owner of a previously deployed OML in-database model.
- B. Change the namespace of a previously deployed OML in-database model.
- C. Undeploy a previously deployed OML in-database model.
- D. Delete an existing OML in-database model.
- E. Deploy an existing Oracle Machine Learning in-database model as a REST endpoint in OML Services.
- F. Change the deployment date of a previously deployed OML in-database model.
Answer: B,C,D,E
Explanation:
Explanation
https://learn.oracle.com/ols/course/using-oracle-machine-learning-with-autonomous-database/35644/98086/1493
NEW QUESTION # 25
In which three use cases are Oracle Machine Learning algorithms suitable? (Choose three.)
- A. Medical outcome analysis
- B. Anomaly and fraud detection
- C. Speech recognition
- D. Customer segmentation
- E. Graph analytics
Answer: A,B,D
Explanation:
* Oracle Machine Learning algorithms are suitable for various use cases that involve data analysis, prediction, classification, clustering, association, and feature extraction56.
* Three use cases that are suitable for Oracle Machine Learning algorithms are:
* Medical outcome analysis: This is a use case that involves predicting the outcome of a medical treatment or procedure based on patient characteristics and medical history. Oracle Machine Learning algorithms such as Generalized Linear Models, Support Vector Machines, or Neural Networks can be used for this task.
* Anomaly and fraud detection: This is a use case that involves identifying unusual or suspicious patterns or behaviors in data that may indicate fraud, abuse, or errors. Oracle Machine Learning algorithms such as One-Class Support Vector Machines, Anomaly Detection, or Principal Component Analysis can be used for this task.
* Customer segmentation: This is a use case that involves grouping customers based on their similarities in terms of demographics, preferences, behaviors, or needs. Oracle Machine Learning algorithms such as K-Means, Expectation Maximization, or Non-Negative Matrix Factorization can be used for this task.
NEW QUESTION # 26
When managing Machine Learning models using the OML AutoML UI, what are the three actions that can be performed on Oracle Machine Learning (OML) models from within OML AutoML UI? (Choose three.)
- A. Review the model statistics associated with the experiment of an OML in-database model.
- B. Deploy an OML in-database model to a REST endpoint.
- C. Review the model statistics associated with the experiment of an ONNX-format (Open Neural Networks Exchange) model.
- D. Review the model statistics associated with the experiment of an ONNX-format image classification model.
- E. Create a notebook with auto-generated OML4Py code from an OML in-database mod-el to allow for further model tweaking and batch scoring.
Answer: A,B,E
Explanation:
Explanation
When managing machine learning models using the OML AutoML UI, three actions that can be performed on Oracle Machine Learning (OML) models from within OML AutoML UI are:
* Create a notebook with auto-generated OML4Py code from an OML in-database model to allow for further model tweaking and batch scoring. This feature enables users to export the selected model as a notebook that contains the OML4Py code to reproduce the model building process and perform additional tasks such as model evaluation, scoring, or deployment1.
* Deploy an OML in-database model to a REST endpoint. This feature enables users to deploy the selected model as a RESTful web service that can be accessed by external applications or tools for real-time scoring or predictions2.
* Review the model statistics associated with the experiment of an OML in-database model. This feature
* enables users to view the details of the model such as the algorithm name, hyperparameters, performance metrics, feature importance, and confusion matrix3.
NEW QUESTION # 27
Which four actions would typically be performed during the data preparation step for analyzing data with Oracle Machine Learning?
- A. performing feature engineering, such as creating derived variables
- B. binning of numeric data
- C. numeric data normalization
- D. missing value replacement
- E. data collection from various sources
- F. building a machine learning model
Answer: A,B,C,D
Explanation:
* The data preparation step for analyzing data with Oracle Machine Learning involves various actions to transform the raw data into a suitable format for machine learning algorithms45.
* Some of the actions that would typically be performed during the data preparation step are:
* Numeric data normalization: This is a technique for reducing the range of numerical data by mapping them to a standard scale, such as 0 to 1. Normalization can improve the performance and stability of some machine learning algorithms5.
* Missing value replacement: This is a technique for handling missing or null values in the data, which can cause errors or bias in some machine learning algorithms. Missing values can be replaced by various methods, such as mean, median, mode, or a constant value4.
* Performing feature engineering, such as creating derived variables: This is a technique for creating new features from existing ones or combining them in meaningful ways. Feature engineering can enhance the predictive power and interpretability of machine learning models4.
* Binning of numeric data: This is a technique for reducing the cardinality of continuous and discrete data by grouping related values together in bins. Binning can improve resource utilization and model build response time without significant loss in model quality. Binning can also strengthen the relationship between attributes and improve model quality5
NEW QUESTION # 28
What is the correct sequence of creating items in Oracle Machine Learning (OML) Note-books when setting up a new Autonomous Database instance?
- A. Notebook, Job, Project, OML User
- B. Workspace, OML User, Notebook, Jobs
- C. Job, Project, Workspace, Notebook
- D. OML User, Notebook, Job
Answer: B
Explanation:
* The correct sequence of creating items in Oracle Machine Learning Notebooks when setting up a new Autonomous Database instance is Workspace, OML User, Notebook, Jobs1.
* A workspace is a logical container for organizing and managing notebooks, jobs, and projects. A workspace can be shared by multiple users with different roles and permissions1.
* An OML user is a database user who has access to Oracle Machine Learning Notebooks. An administrator needs to create an OML username and password for each user in the Oracle Machine Learning User Management interface2.
* A notebook is a document that contains SQL, PL/SQL, Python, or R code, as well as text, images, charts, and graphs. A notebook can be used for data exploration, data visualization, data preparation, and machine learning3.
* A job is a scheduled execution of a notebook or a script. A job can run on a recurring schedule or on demand. A job can also send notifications to users via email or webhooks4.
NEW QUESTION # 29
Which three statements are true about Oracle Machine Learning Notebooks? (Choose three.)
- A. It is used to access machine learning algorithms.
- B. It is used for data preparation and exploration.
- C. It provides a web-based interface for data analysis.
- D. It is used to manage and monitor database objects.
- E. It is used to create low-code applications.
Answer: A,B,C
Explanation:
Explanation
https://www.doag.org/formes/pubfiles/13151859/OE-DAC-Oracle-Machine-Learning-Overview-Whats-New-Cu
NEW QUESTION # 30
Which three are supervised machine learning algorithms? (Choose three.)
- A. Linear Regression
- B. Association rule
- C. Random Forest
- D. K-means clustering
- E. Support Vector Machines
Answer: A,C,E
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml4py/1/mlpug/about-machine-learning-algorithm
NEW QUESTION # 31
Which three types of templates are available in Oracle Machine Learning Notebooks? (Choose three.)
- A. Example templates
- B. Shared templates
- C. Personal templates
- D. Custom templates
- E. Public templates
Answer: A,B,C
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/use-library-collaborate-users
NEW QUESTION # 32
A user with Developer permission is trying to create a job on an existing notebook that is shared. However, the user is unable to do so. What is the reason?
- A. A developer cannot create jobs for notebooks that are shared.
- B. The specified job already exists.
- C. The user requires the Create Job role.
- D. The notebook contains code with syntax errors, which need to be corrected first.
Answer: C
Explanation:
* The reason why a user with Developer permission is unable to create a job on an existing notebook that is shared is that the user requires the Create Job role1.
* The Create Job role is a database role that grants the privilege to create and manage jobs on Oracle Machine Learning Notebooks. This role is not granted by default to any user, including the ADMIN user. An administrator needs to explicitly grant this role to users who need to create jobs1
NEW QUESTION # 33
Which step is not required to be performed by an administrator when adding a new user to Oracle Machine Learning (OML) Notebooks?
- A. Add the user's name and email ID in the Oracle Machine Learning User Management interface.
- B. Provide the user with Autonomous Database client wallet for remote credentials.
- C. Issue grant commands on tables from other schemas to allow access from shared note-books.
- D. Create an OML username and password for the user in the Oracle Machine Learning User Management interface.
Answer: B
Explanation:
* The step that is not required to be performed by an administrator when adding a new user to Oracle Machine Learning Notebooks is providing the user with Autonomous Database client wallet for remote credentials.
* The client wallet is only needed for remote access to the database using tools such as SQL Developer or Python. For accessing Oracle Machine Learning Notebooks, the user only needs an OML username and password, which are created by the administrator in the Oracle Machine Learning User Management interface
NEW QUESTION # 34
An OML AutoML UI Experiment is a work unit that minimally contains the definition of which three options?
(Choose three.)
- A. Algorithm
- B. Prediction Type
- C. Data Source
- D. Prediction Target
- E. Parameters
Answer: B,C,D
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-automl-ui/amlui/create-experiment.html
NEW QUESTION # 35
Which type of user has access to the Oracle Machine Learning User Management interface?
- A. Manager
- B. Developer
- C. Administrator
- D. Guest
Answer: C
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml4sql/21/mlsql/access-autonomous-database.htm
NEW QUESTION # 36
Which two statements are true about Classification algorithms? (Choose two.)
- A. They predict numeric values along a continuum.
- B. They require known outcomes to guide the learning process.
- C. They extract rules using unsupervised learning.
- D. They assign cases to target categories.
Answer: B,D
Explanation:
* Classification algorithms are supervised learning methods that assign cases to target categories based on a set of input features12. For example, a classification algorithm can predict whether an email is spam or not based on its content and sender.
* Classification algorithms require known outcomes to guide the learning process, which means they need labeled data for training and evaluation12. For example, a classification algorithm can learn from a set of emails that are already labeled as spam or not by humans
NEW QUESTION # 37
Which is a FALSE statement regarding Oracle Machine Learning (OML)?
- A. OML provides univariate and multivariate statistics.
- B. OML provides integration with open source Python and R statistical analysis functions.
- C. OML offerings need a separate data visualization tool for creating visualization.
- D. OML provides scalable statistical functions though OML4Py and OML4R.
Answer: C
Explanation:
* A false statement regarding Oracle Machine Learning (OML) is that OML offerings need a separate data visualization tool for creating visualization56.
* OML does not need a separate data visualization tool for creating visualization because it provides various options for visualizing data and models within its offerings. For example, OML Notebooks support interactive charts and graphs using Plotly and Matplotlib libraries for Python and R.
OML SQL also supports native SQL functions for creating histograms, scatter plots, box plots, and more
NEW QUESTION # 38
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