Real 1z0-1096-23 dumps Accurate Questions and Answers with Free and Fast Updates
Real 1z0-1096-23 Quesions Pass Certification Exams Easily
Oracle 1z0-1096-23 Exam Syllabus Topics:
| Topic | Details |
|---|---|
| Topic 1 |
|
| Topic 2 |
|
| Topic 3 |
|
| Topic 4 |
|
| Topic 5 |
|
| Topic 6 |
|
| Topic 7 |
|
| Topic 8 |
|
| Topic 9 |
|
| Topic 10 |
|
NEW QUESTION # 39
Which two can be performed by an Administrator in Oracle Machine Learning Notebooks? (Choose two.)
- A. Run noteboooks
- B. Manage any notebook
- C. View notebooks in read-only mode
- D. Reassign user workspace
Answer: C,D
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/administer-oracle-machine-le
NEW QUESTION # 40
In which format is an Oracle Machine Learning Notebooks notebook saved or exported?
- A. custom binary format
- B. XML
- C. CSV
- D. JSON
Answer: D
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/notebooks.html
NEW QUESTION # 41
What is the proper workflow for analyzing data in Oracle Machine Learning?
- A. Evaluate the model, prepare the data, build the model, and deploy the model.
- B. Build the model, prepare the data, evaluate the model, and deploy the model.
- C. Prepare the data, build the model, evaluate the model, and deploy the model.
- D. Get predictions from the model, prepare the data, build the model, and deploy the model.
Answer: C
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml4sql/21/mlsql/process-overview.html#GUID-A6 Process Overview: The lifecycle of a machine learning project is divided into six phases. The process begins by defining a business problem and restating the business problem in terms of a machine learning objective.
The end goal of a machine learning process is to produce accurate results for solving your business problem.
Workflow: The machine learning process workflow illustration is based on the CRISP-DM method-ology.
Each stage in the workflow is illustrated with points that summarize the key tasks. The CRISP-DM methodology is the most commonly used methodology for machine learning. The following are the phases of the machine learning process: Define business goals Understand data Pre-pare data Develop models Evaluate Deploy
NEW QUESTION # 42
In an Oracle Machine Learning notebook, which is the correct syntax for starting a SQL script in Scratchpad?
- A. "%sql"
- B. "$sql"
- C. "#sql"
- D. "@sql"
Answer: A
Explanation:
Explanation
%sql - Allows you to run SQL statements. Use the Scratchpad The Scratchpad provides you convenient one-click access to a notebook for running SQL statements, PL/SQL scripts, and Python scripts that can be renamed. The Scratchpad is available on the Oracle Machine Learning Notebooks home page. Note: The Scratchpad is a regular notebook that is prepopulated with three paragraphs - %sql, %script, and %python.
After you run your scripts, the Scratchpad is automatically saved as a notebook by the default name Scratchpad in the Notebooks page. You can access it later in the Notebooks page. You can run all the paragraphs together or one paragraph at a time. To open and use the scratchpad, click Scratchpad on the Oracle Machine Learning Notebooks home page under Quick Actions. The Scratchpad opens. The Scratchpad has three paragraphs each with the following directives:%sql - Allows you to run SQL statements.%script - Allows you to run PL/SQL scripts.%python - Allows you to run Python scripts.
NEW QUESTION # 43
Which three are unsupervised machine learning algorithms? (Choose three.)
- A. Logistical Regression
- B. K-means clustering
- C. Association rule
- D. Random Forest
- E. Naive Bayes
- F. Principal Component Analysis
Answer: B,C,F
Explanation:
Explanation
Unsupervised machine learning uses a more independent approach, in which a computer learns to identify complex processes and patterns without a human providing close, constant guidance. Un-supervised machine learning involves training based on data that does not have labels or a specific, defined output. To continue the childhood teaching analogy, unsupervised machine learning is akin to a child learning to identify fruit by observing colors and patterns, rather than memorizing the names with a teacher's help. The child would look for similarities between images and separate them into groups, assigning each group its own new label.
Examples of unsupervised machine learning algorithms include k-means clustering, principal and independent component analysis, and association rules.
NEW QUESTION # 44
Which two statements are true about Classification algorithms? (Choose two.)
- A. They predict numeric values along a continuum.
- B. They extract rules using unsupervised learning.
- C. They assign cases to target categories.
- D. They require known outcomes to guide the learning process.
Answer: C,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 # 45
You want to segment your customer data for marketing reseach purposes and identify homogeneous groups to build supervised models. What should you use to achieve this?
- A. Classification
- B. Clustering
- C. Regression
- D. Feature Extraction
Answer: B
Explanation:
* To segment your customer data for marketing research purposes and identify homogeneous groups to build supervised models, you should use clustering12.
* Clustering is a type of unsupervised machine learning that groups data points based on their similarities in terms of features or attributes. Clustering can help discover the underlying structure of the data and reveal the natural segments or categories within it12.
* Clustering can be useful for marketing research because it can help identify different types of customers based on their demographics, preferences, behaviors, or needs. Clustering can also help create customer profiles or personas that can be used to target specific segments with tailored marketing campaigns or offers12.
* Clustering can also be used as a preliminary step for building supervised models, such as classification or regression. By using the cluster labels as an additional feature or a target variable, supervised models can learn from the cluster information and improve their accuracy or performance12.
NEW QUESTION # 46
You want to analyze the spike in sales during weekends in India (Saturday and Sunday) and also perform a similar analysis for weekends in Dubai (Friday and Saturday). You will be re-using these notebooks in similar situations over time. You do not want to share them with other users. Which template should you use?
- A. Example
- B. Personal
- C. Public
- D. Shared
Answer: B
Explanation:
Explanation
https://learn.oracle.com/ols/course/using-oracle-machine-learning-with-autonomous-database/35644/98086/1493
NEW QUESTION # 47
Which three types of permissions can be granted to a user to callaborate and access a workspace in Oracle Machine Learning Notebooks?
- A. Developer
- B. Viewer
- C. Administrator
- D. Manager
- E. Guest
Answer: A,B,D
Explanation:
* The three types of permissions that can be granted to a user to collaborate and access a workspace in Oracle Machine Learning Notebooks are Viewer, Manager, and Developer1.
* Viewer is a user role that allows users to view notebooks but not run or modify them1.
* Manager is a user role that allows users to perform all the tasks of a Developer as well as manage other users' workspaces and permissions1.
* Developer is a user role that allows users to create and run notebooks, run SQL statements, create SQL scripts, run Python scripts, create jobs to schedule and run notebooks, use example template notebooks, create and run AutoML experiments, and deploy models1.
NEW QUESTION # 48
Which three tasks can be performed by an Oracle Machine Learning (OML) user with the Developer role?
(Choose three.)
- A. Edit Example templates.
- B. Transfer OML workspace to other users.
- C. Create and run scratchpads.
- D. Share notebooks.
- E. Create other OML users.
- F. Create and run OML notebooks.
Answer: B,D,F
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/administer-oracle-machine-le
NEW QUESTION # 49
Which output formats are supported by the SET SQLFORMAT command? (Choose three.)
- A. CSV
- B. TXT
- C. HTML
(Correct) - D. JSON
Answer: A,D
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/output-formats-supported-set
NEW QUESTION # 50
Which two statements are true about OML AutoML UI? (Choose two.)
- A. An Experiment can be run with two possible options: Faster Results or Better Accuracy.
- B. When creating a notebook from an experiment-produced Model, the top algorithm in the Leader Board is automatically selected and converted to OML4Py code.
- C. Automates key modeling steps such as algorithm selection, feature selection, and hyperparameter tuning.
- D. An Experiment returns a single machine learning model, on successful execution Pro-vides Classification Prediction Type for numeric data and Regression Prediction Type for non-numeric data.
Answer: A,C
Explanation:
Explanation
https://www.oracle.com/a/tech/docs/otn-batch1/oml-automl-ui-tech-brief.pdf
https://docs.oracle.com/en/database/oracle/machine-learning/oml-automl-ui/amlui/create-experiment.html
NEW QUESTION # 51
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. Export the notebook and import it into the other user's project
- B. Provide the user Viewer permission to your workspace
- C. Provide the user Developer permission to your workspace.
- D. Share the notebook as a Shared Oracle Machine Learning Template
Answer: A,B,D
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/collaborate-oracle-machine-l
NEW QUESTION # 52
To navigate to a specific notebook provided by another user, which is the correct workflow?
- A. Change user > Open notebook > Create project
- B. Change project > Change workspace > Open notebook
- C. Create user > Change workspace > Open notebook
- D. Select workspace > Select project > List notebooks > Open notebook
Answer: D
Explanation:
Explanation
https://apexapps.oracle.com/pls/apex/dbpm/r/livelabs/view-workshop?wid=891&clear=180&session=109742845
NEW QUESTION # 53
What is the correct sequence of creating items in Oracle Machine Learning (OML) Note-books when setting up a new Autonomous Database instance?
- A. Job, Project, Workspace, Notebook
- B. OML User, Notebook, Job
- C. Workspace, OML User, Notebook, Jobs
- D. Notebook, Job, Project, OML User
Answer: C
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 # 54
You have created a workspace in Oracle Machine Learning Notebooks and want to share it with collaborators by granting permissions to access your workspace. You want to enable other users to run and modify your notebooks but do not want to provide the ability to schedule jobs that run your notebooks. Which permission type should be granted to this user?
- A. Developer
- B. Manager
- C. Designer
- D. Viewer
Answer: A
Explanation:
Explanation
About Workspace Permission Types: Oracle Machine Learning allows three types of permissions. Depending on the permission type, you can allow the user to view or perform different tasks in your workspace, projects, and notebooks. The three types of permissions are listed in the following table along with the actions that are allowed. Permission Types || Actions based on permission > Manager: * Project: Create, update, delete. * Workspace: View only. * Notebooks: Create, update, run, delete, and schedule jobs. > Developer: * Project:
View only. * Workspace: View only. * Notebooks: Create, update, run, and delete notebooks that a developer creates only. * Jobs: View and run jobs of shared notebooks only. A developer cannot create jobs for notebooks that are shared. > Viewer: * Project: View only. * Workspace: View only. * Notebooks: View only. * Jobs: View jobs and job runs of shared notebooks only.
NEW QUESTION # 55
Which two are required by an administrator while adding a new user to Oracle Machine Learning (OML) Notebooks? (Choose two.)
- A. User's name and email ID
- B. Privileges to be provided
- C. Wallet information to connect to ADB
- D. Autonomous Database (ADB) name
- E. OML username and password
Answer: A,E
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/administer-oracle-machine-le Create User: An administrator creates a new user account and user credentials for Oracle Machine Learning in the User Management interface. Note: You must have the administrator role to access the Oracle Machine Learning User Management interface. To create a user account: Select an Autonomous Da-ta Warehouse instance and on the details page click Service Console. On the Service Console click Administration. Click Manage OML Users to open the Oracle Machine Learning User Administration page. Click Create on the Oracle Machine Learning User Administration page. In the Username field, enter a username for the account.
Using the username, the user will log in to an Oracle Ma-chine Learning instance. Enter a name in the First Name field. Enter a name in the Last Name field. In the Email Address field, enter the email ID of the user.
Select the option Generate password and email account details to user. User will be required to reset the password on first sign in. to auto generate a temporary password and send an email with the account credentials to the user. If you select this option, you need not enter values in the Password and Confirm Password fields; the fields are grayed out. In the Password field, enter a password for the user, if you choose to create a password for the user.This option is disabled if you select the Generate password... option to auto generate a temporary password for the user. In the Confirm Password field, enter a password to confirm the value that you entered in the Password field.By doing so, you create the password for the user. The user can change the password when first logging in. Click Create. This creates a new database user and grants the required privileges to use Oracle Machine Learning.
NEW QUESTION # 56
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 # 57
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 (Regression)
- B. Explicit Semantic Analysis
- C. Support Vector Machine (Regression)
- D. Neural Networks (Regression)
- E. One-Class Support Vector Machine
- F. Generalized Linear Model (Classification)
Answer: A,C,D
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 # 58
Which three data sources can be immediately used for model building in Oracle Machine Learning? (Choose three.)
- A. Oracle Database views
- B. Oracle Database tables
- C. JSON files
- D. Oracle Database External tables
- E. CSV files
Answer: B,C,E
Explanation:
Explanation
The three data sources that can be immediately used for model building in Oracle Machine Learning are:
Oracle Database tables: Oracle Machine Learning can directly access and use data from tables within an Oracle Database for model building. This allows for efficient utilization of the database's structured data for machine learning tasks. Oracle Database views: Similar to tables, Oracle Machine Learning can also utilize data from database views. Views provide a virtual representation of the data, allowing users to access and analyze specific subsets or transformations of the underlying tables. CSV files: Oracle Machine Learning supports the use of CSV (Comma-Separated Values) files as a data source for model building. CSV files provide a simple and widely-used format for storing tabular data, making it easy to import and use within Oracle Machine Learning. Therefore, the correct options are: Oracle Database tables Oracle Database views CSV files
NEW QUESTION # 59
Which three types of forms are available in Oracle Machine Learning Notebooks? (Choose three.)
- A. Text Input form
- B. Check Box form
- C. List form
- D. Radio form
- E. Select form
Answer: A,B,E
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/create-check-box-forms.html
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/create-select-forms.html
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/create-text-input-forms.html
NEW QUESTION # 60
......
1z0-1096-23 Dumps are Available for Instant Access: https://www.updatedumps.com/Oracle/1z0-1096-23-updated-exam-dumps.html
Practice with these 1z0-1096-23 dumps Certification Sample Questions: https://drive.google.com/open?id=1gJwEjBUSwRg2aOUUmqfdE839ZNYG5Ww9