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NEW QUESTION # 40
In which three use cases are Oracle Machine Learning algorithms suitable? (Choose three.)
- A. Graph analytics
- B. Anomaly and fraud detection
- C. Medical outcome analysis
- D. Customer segmentation
- E. Speech recognition
Answer: B,C,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 # 41
Which three types of forms are available in Oracle Machine Learning Notebooks? (Choose three.)
- A. Text Input form
- B. Select form
- C. Radio form
- D. List form
- E. Check Box 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 # 42
An OML AutoML UI Experiment is a work unit that minimally contains the definition of which three options?
(Choose three.)
- A. Algorithm
- B. Data Source
- C. Prediction Target
- D. Prediction Type
- 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 # 43
Which three services can be used to access Oracle Machine Learning Notebooks? (Choose three.)
- A. Autonomous Transaction Processing
- B. Autonomous Data Warehouse
- C. Oracle Application Express
- D. Autonomous Dedicated Infrastructure
- E. Autonomous JSON Database
Answer: A,B,E
Explanation:
Explanation
Oracle Machine Learning Notebooks Increase data scientist and developer productivity and reduce their learning curve with familiar open source-based Apache Zeppelin notebook technology. Note-books support SQL, PL/SQL, Python, and markdown interpreters for Oracle Autonomous Database so users can work with their language of choice when developing models. View interactive product tour Oracle Machine Learning Notebooks with Autonomous Data Warehouse documentation Oracle Machine Learning Notebooks with Autonomous Transaction Processing documentation Oracle Ma-chine Learning Notebooks with Autonomous JSON Database documentation
NEW QUESTION # 44
How can you share a notebook with multiple developers for a collaborative effort with note-book editing?
- A. Notebooks cannot be shared for collaborating with other users.
- B. You can share notebooks if you have Viewer permissions.
- C. You can share notebooks if you have Developer permissions.
- D. You create different notebooks, edit separately, and merge later.
Answer: C
Explanation:
Explanation
You can also collaborate by exporting your notebook as a JSON or JavaScript Object Notation file. This exported file can be imported into the same or different environment. To export a notebook as a JSON file, open the notebook in the notebook editor, click on the Export icon. A Save As dialog will open where you can specify the name of the JSON file and location on your system.
NEW QUESTION # 45
You have created a notebook and want to run the notebook on a periodic schedule. How should you achieve this?
- A. You can create a job and schedule it to run a specific notebook.
- B. You cannot run the notebook on the scheduled time.
- C. You need to contact the database administrator to configure the notebook to run at a particular time.
- D. You have to login as the admin user and schedule a job to run the notebook.
Answer: A
Explanation:
Explanation
Jobs allow you to schedule the running of notebooks. In the Jobs page, you can create jobs, duplicate jobs, start and stop jobs, delete jobs, and monitor job status by viewing job logs, which are read-only notebooks.
About Jobs. The Jobs page lists all the jobs created, along with the job name, notebook, owner of the job, last start date, next run date, status, and schedule. Create Jobs to Schedule Notebooks You can create jobs to schedule your notebook with preferred scheduling set-tings. View Job Logs You can view the historical logs of any particular job in the Job Log interface. About Jobs The Jobs page lists all the jobs created, along with the job name, notebook, owner of the job, last start date, next run date, status, and schedule.
NEW QUESTION # 46
Which three actions can be performed by an Administrator in Oracle Machine Learning (OML) Notebooks?
(Choose three.)
- A. View notebooks.
- B. Create, run and delete notebooks.
- C. Create, edit and delete OML users.
- D. Create and run jobs.
- E. Reassign workspaces to users.
Answer: A,C,E
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/administer-oracle-machine-le
* View notebooks. An Administrator can view notebooks in their own workspace or in workspaces where they have collaboration rights. However, an Administrator cannot run or modify notebooks1.
* Reassign workspaces to users. An Administrator can reassign workspaces from one user to another user in the User Data page. This can be useful when a user leaves the organization or changes roles2.
* Create, edit and delete OML users. An Administrator can create new OML user accounts and passwords, edit existing OML user information, and delete OML users in the User Management interface.
NEW QUESTION # 47
Which option would you use to load data from Object Storage into an Oracle Autonomous Database?
- A. DBMS_Cloud package
- B. Oracle SQL Developer Web
- C. Expdp
- D. SQL*Loader
Answer: A
Explanation:
Explanation
About Data Loading: Autonomous Database provides the following loading options: You can load data using Oracle Database Actions. You can load data using Oracle Database tools and Oracle or other 3rd party data integration tools. On transaction processing systems you traditionally ingest data through routine transactions or with DML operations. In general you load data from files local to your client computer or from files stored in a cloud-based object store. To load data from files in the cloud, use either Oracle Database Actions or use the Autonomous Database PL/SQL package DBMS_CLOUD to load files from the cloud. For the fastest data loading experience Oracle recommends uploading the source files to a cloud-based object store, such as Oracle Cloud Infrastructure Object Storage, before loading the data into your database. Oracle provides support for loading files that are located locally in your data center, but when using this method of data loading you should factor in the transmission speeds across the Internet which may be significantly slower. For more information on Oracle Cloud Infrastructure Object Storage, see Putting Data into Object Storage and Overview of Object Storage. Note: If you are not using ADMIN user, ensure the user has the necessary privileges for the operations the user needs to perform. See Manage User Privileges on Autonomous Database - Connecting with a Client Tool for more information.
NEW QUESTION # 48
Which three statements are true about unsupervised machine learning? (Choose three.)
- A. There is no previously known result to guide the algorithm in building the model.
- B. It uses unlabeled data.
- C. It can be used as a preliminary step for supervised algorithms.
- D. It analyzes cases where the target value is already known.
Answer: A,B,C
Explanation:
* Unsupervised machine learning is a type of machine learning in which algorithms learn patterns exclusively from unlabeled data34. Unsupervised learning algorithms discover hidden structures or groupings in the data without any supervision or guidance from human experts34.
* Three statements that are true about unsupervised machine learning are:
* There is no previously known result to guide the algorithm in building the model. Unsupervised learning algorithms do not have any predefined target variable or outcome to optimize. They rely on the intrinsic properties of the data to find meaningful patterns or clusters34.
* It can be used as a preliminary step for supervised algorithms. Unsupervised learning algorithms can be useful for exploratory data analysis, feature extraction, dimensionality reduction, or data preprocessing before applying supervised learning algorithms34.
* It uses unlabeled data. Unsupervised learning algorithms do not require any labeled data or annotations to learn from. They can work with raw or unstructured data such as text, images, audio, or video34.
NEW QUESTION # 49
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. Prepare the data, build the model, evaluate the model, and deploy the model.
- C. Get predictions from the model, prepare the data, build the model, and deploy the model.
- D. Build the model, prepare the data, evaluate the model, and deploy the model.
Answer: B
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 # 50
Which three types of templates are available in Oracle Machine Learning Notebooks? (Choose three.)
- A. Public templates
- B. Shared templates
- C. Example templates
- D. Personal templates
- E. Custom templates
Answer: B,C,D
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/use-library-collaborate-users
NEW QUESTION # 51
Which two components support in-database automatic machine learning (AutoML) functionality?
- A. OML4Py
- B. OML4R
- C. OML Services
- D. OML4SQL
- E. Oracle Data Miner
- F. OML AutoML UI
Answer: A,F
Explanation:
Explanation
https://blogs.oracle.com/machinelearning/post/introducing-oml-automl-user-interface
https://www.oracle.com/a/tech/docs/technical-resources/oml-technical-brief.pdf
NEW QUESTION # 52
Which output formats are supported by the SET SQLFORMAT command? (Choose three.)
- A. HTML
(Correct) - B. TXT
- 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 # 53
Which three are unsupervised machine learning algorithms? (Choose three.)
- A. Logistical Regression
- B. Naive Bayes
- C. Random Forest
- D. Association rule
- E. K-means clustering
- F. Principal Component Analysis
Answer: D,E,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 # 54
Which task is NOT required by an Administrator when adding a new user to Oracle Ma-chine Leamina (OML) Notebooks?
- A. Create an OML username and password for the user in the Oracle Machine Learning Management User Interface.
- B. Add the user's full name and email ID in the Oracle Machine Learning Management User Interface.
- C. Provide the user with an Autonomous Data Warehouse client wallet for remote authentication.
- D. Issue grant commands on the database to allow access to the tables associated with the user's Oracle Machine Learning Notebooks.
Answer: C
Explanation:
* The task that is NOT required by an administrator when adding a new user to Oracle Machine Learning Notebooks is providing the user with an Autonomous Data Warehouse client wallet for remote authentication3.
* 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 interface3.
NEW QUESTION # 55
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. Feature Extraction
- B. Classification
- C. Clustering
- D. Regression
Answer: C
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 # 56
Which is a FALSE statement regarding Oracle Machine Learning (OML)?
- A. OML provides scalable statistical functions though OML4Py and OML4R.
- B. OML offerings need a separate data visualization tool for creating visualization.
- C. OML provides integration with open source Python and R statistical analysis functions.
- D. OML provides univariate and multivariate statistics.
Answer: B
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 # 57
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 # 58
For which two types of notebooks can you schedule a job? (Choose two.)
- A. Notebooks shared with you
- B. Notebooks under Personal templates
- C. Notebooks owned by you
- D. Notebooks under Shared templates
Answer: A,C
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: Cre-ate, 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 # 59
Which three SQL commands are restricted in an Autonomous Database?
- A. Alter Profile
- B. Create Tablespace
- C. Alter Tablespace
- D. Alter Table
- E. Create Table
Answer: A,B,C
Explanation:
Explanation
https://docs.oracle.com/en/cloud/paas/autonomous-database/adbsa/autonomous-sql-commands.html
NEW QUESTION # 60
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