1z0-1096-23 Self-Study Guide for Becoming an Oracle Machine Learning using Autonomous Database 2023 Associate Expert
1z0-1096-23 Study Guide Realistic Verified 1z0-1096-23 Dumps
NEW QUESTION # 33
Which four statements are true about Oracle Machine Learning on Oracle Autonomous Database? (Choose four.)
- A. It is deployed with Oracle Data Miner.
- B. It provides a collaborative web-based notebook interface.
- C. It provides an interface to monitor a database.
- D. It provides a development environment to build models and score data.
- E. It includes parallelized in-database algorithms.
- F. It enables data analytics, data discovery, and data visualizations.
Answer: B,D,E,F
Explanation:
Explanation
https://docs.oracle.com/en/cloud/paas/autonomous-database/adbsa/autonomous-oml.html#GUID-63F2D68B-6D
NEW QUESTION # 34
(PICq21) Examine the output: <PIC>
- A. SET SQLFORMAT DELIMITED
- B. SET SQLFORMAT LOADER
- C. SET SQLFORMAT ANSICONSOLE
- D. SET SQLFORMAT FIXED
Answer: B
Explanation:
Explanation
https://oracle-base.com/articles/misc/sqlcl-format-query-results-with-the-set-sqlformat-command#loader
NEW QUESTION # 35
Which two can be performed by an Administrator in Oracle Machine Learning Notebooks? (Choose two.)
- A. View notebooks in read-only mode
- B. Run noteboooks
- C. Reassign user workspace
- D. Manage any notebook
Answer: A,C
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/administer-oracle-machine-le
NEW QUESTION # 36
Which three are unsupervised machine learning algorithms? (Choose three.)
- A. K-means clustering
- B. Principal Component Analysis
- C. Logistical Regression
- D. Naive Bayes
- E. Random Forest
- F. Association rule
Answer: A,B,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 # 37
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. Feature Extraction
- 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 # 38
Which two components support in-database automatic machine learning (AutoML) functionality?
- A. OML4Py
- B. OML AutoML UI
- C. Oracle Data Miner
- D. OML Services
- E. OML4R
- F. OML4SQL
Answer: A,B
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 # 39
Which four actions would typically be performed during the data preparation step for analyzing data with Oracle Machine Learning?
- A. numeric data normalization
- B. data collection from various sources
- C. missing value replacement
- D. binning of numeric data
- E. building a machine learning model
- F. performing feature engineering, such as creating derived variables
Answer: A,C,D,F
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 # 40
Which output formats are supported by the SET SQLFORMAT command? (Choose three.)
- A. HTML
(Correct) - B. JSON
- C. TXT
- D. CSV
Answer: B,D
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/output-formats-supported-set
NEW QUESTION # 41
Which statement is FALSE about Oracle Machine Learning (OML) Notebooks?
- A. You can set the output format in SQL paragraphs of a notebook.
- B. 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.
- C. Within notebook paragraphs you can switch between data views of tables, pie charts, bar charts, line plots and scatter plots.
- D. You can share notebooks with Import/Export operations.
Answer: B
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 # 42
Which three types of forms are available in Oracle Machine Learning Notebooks? (Choose three.)
- A. Select form
- B. List form
- C. Radio form
- D. Text Input form
- E. Check Box form
Answer: A,D,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 # 43
Which type of user has access to the Oracle Machine Learning User Management interface?
- A. Developer
- B. Administrator
- C. Guest
- D. Manager
Answer: B
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml4sql/21/mlsql/access-autonomous-database.htm
NEW QUESTION # 44
In which three use cases are Oracle Machine Learning algorithms suitable? (Choose three.)
- A. Anomaly and fraud detection
- B. Graph analytics
- C. Customer segmentation
- D. Medical outcome analysis
- E. Speech recognition
Answer: A,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 # 45
Which three actions can be performed by an Administrator in Oracle Machine Learning (OML) Notebooks?
(Choose three.)
- A. Create and run jobs.
- B. View notebooks.
- C. Create, edit and delete OML users.
- D. Reassign workspaces to users.
- E. Create, run and delete notebooks.
Answer: B,C,D
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 # 46
What are three key features of Oracle Machine Learning Notebooks? (Choose three.)
- A. They provide a collaborative notebook interface on Oracle Autonomous Database.
- 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 support SQL, PL/SQL, JavaScript, and PHP scripting languages.
Answer: A,C,D
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/
NEW QUESTION # 47
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. Provide the user Viewer permission to your workspace
- B. Provide the user Developer permission to your workspace.
- C. Share the notebook as a Shared Oracle Machine Learning Template
- D. Export the notebook and import it into the other user's project
Answer: A,C,D
Explanation:
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/collaborate-oracle-machine-l
NEW QUESTION # 48
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 notebook contains code with syntax errors, which need to be corrected first.
- D. The user requires the Create Job role.
Answer: D
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 # 49
What is the correct sequence of creating items in Oracle Machine Learning (OML) Note-books when setting up a new Autonomous Database instance?
- A. OML User, Notebook, Job
- B. Workspace, OML User, Notebook, Jobs
- C. Job, Project, Workspace, Notebook
- D. Notebook, Job, Project, OML User
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 # 50
Which type of machine learning algorithm is used to deal with noise in incoming data?
- A. Classification
- B. Dimensionality Reduction
- C. Clustering
- D. Regression
Answer: B
Explanation:
Explanation
https://blogs.oracle.com/machinelearning/post/using-svd-for-dimensionality-reduction
NEW QUESTION # 51
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