究極のガイド準備1z0-1096-23認証試験Oracle Databaseは2024年更新
リアル1z0-1096-23問題集でOracle正確なアンサーは最新問題は2024年更新
質問 # 14
What is the correct sequence of function invocations of AutoML API from OML4Py to solve a business problem?
- A. Algorithm selection, Feature selection. Model tuning
- B. Model selection, Algorithm selection
- C. Model tuning. Algorithm selection. Feature selection
- D. Model selection, Algorithm selection
正解：A
解説：
Explanation
https://www.doag.org/formes/pubfiles/13151859/OE-DAC-Oracle-Machine-Learning-Overview-Whats-New-Cu
質問 # 15
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. performing feature engineering, such as creating derived variables
- D. binning of numeric data
- E. missing value replacement
- F. building a machine learning model
正解：A、C、D、E
解説：
* 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
質問 # 16
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"
正解：D
解説：
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.
質問 # 17
Which is NOT a supervised learning algorithm?
- A. Support Vector Machines
- B. Stepwise Linear Regression
- C. Native Bayes
- D. Hierarchical K-Means
- E. Decision Tree
正解：D
解説：
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml4py/1/mlpug/about-machine-learning-algorithm
質問 # 18
Which two Oracle Cloud services are Integrated with Oracle Machine Learning? (Choose two.)
- A. Oracle Analytics Cloud
- B. Oracle GoldenGate
- C. Oracle Autonomous Database
- D. Oracle Stream Analytics
正解：A、C
解説：
* Oracle Analytics Cloud and Oracle Autonomous Database are two Oracle Cloud services that are integrated with Oracle Machine Learning12.
* Oracle Analytics Cloud is a comprehensive cloud service that provides a unified platform for data preparation, analysis, visualization, and machine learning. It supports Oracle Machine Learning Notebooks, which enable data scientists and other data professionals to work collaboratively using SQL, PL/SQL, Python, and R1.
* Oracle Autonomous Database is a self-driving, self-securing, and self-repairing cloud service that supports various workloads such as data warehousing, transaction processing, and JSON document storage. It includes Oracle Machine Learning Services, which enable users to build, deploy, and manage machine learning models using REST APIs2.
質問 # 19
Which three statements are true about unsupervised machine learning? (Choose three.)
- A. It uses unlabeled data.
- B. It analyzes cases where the target value is already known.
- C. It can be used as a preliminary step for supervised algorithms.
- D. There is no previously known result to guide the algorithm in building the model.
正解：A、C、D
解説：
* 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.
質問 # 20
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. Create a notebook with auto-generated OML4Py code from an OML in-database mod-el to allow for further model tweaking and batch scoring.
- B. Deploy an OML in-database model to a REST endpoint.
- C. Review the model statistics associated with the experiment of an OML in-database model.
- D. Review the model statistics associated with the experiment of an ONNX-format (Open Neural Networks Exchange) model.
- E. Review the model statistics associated with the experiment of an ONNX-format image classification model.
正解：A、B、C
解説：
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.
質問 # 21
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. Personal
- B. Example
- C. Public
- D. Shared
正解：A
解説：
Explanation
https://learn.oracle.com/ols/course/using-oracle-machine-learning-with-autonomous-database/35644/98086/1493
質問 # 22
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. Job, Project, Workspace, Notebook
- C. Notebook, Job, Project, OML User
- D. Workspace, OML User, Notebook, Jobs
正解：D
解説：
* 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.
質問 # 23
Which three SQL commands are restricted in an Autonomous Database?
- A. Create Table
- B. Alter Profile
- C. Create Tablespace
- D. Alter Tablespace
- E. Alter Table
正解：B、C、D
解説：
Explanation
https://docs.oracle.com/en/cloud/paas/autonomous-database/adbsa/autonomous-sql-commands.html
質問 # 24
Which two types of permissions allow you tables and run any script on an owner's account? (Choose two.)
- A. Manager
- B. Guest
- C. Developer
- D. Viewer
正解：A、C
解説：
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
質問 # 25
Which three actions can be performed by an Administrator in Oracle Machine Learning (OML) Notebooks?
(Choose three.)
- A. Create, edit and delete OML users.
- B. Create, run and delete notebooks.
- C. Reassign workspaces to users.
- D. View notebooks.
- E. Create and run jobs.
正解：A、C、D
解説：
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.
質問 # 26
Which three types of permissions can be granted to a user to callaborate and access a workspace in Oracle Machine Learning Notebooks?
- A. Viewer
- B. Manager
- C. Administrator
- D. Guest
- E. Developer
正解：A、B、E
解説：
* 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.
質問 # 27
Which two components support in-database automatic machine learning (AutoML) functionality?
- A. OML4Py
- B. Oracle Data Miner
- C. OML4R
- D. OML AutoML UI
- E. OML4SQL
- F. OML Services
正解：A、D
解説：
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
質問 # 28
Which machine learning algorithm allows the system to identify patterns within data sets on its own?
- A. Semi-supervised Learning
- B. Unsupervised Learning
- C. Supervised Learning
- D. Reinforcement Learning
正解：B
解説：
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml4sql/21/mlsql/oracle-machine-learning-sql-guid
質問 # 29
In which three use cases are Oracle Machine Learning algorithms suitable? (Choose three.)
- A. Medical outcome analysis
- B. Graph analytics
- C. Customer segmentation
- D. Anomaly and fraud detection
- E. Speech recognition
正解：A、C、D
解説：
* 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.
質問 # 30
Which option would you use to load data from Object Storage into an Oracle Autonomous Database?
- A. Oracle SQL Developer Web
- B. SQL*Loader
- C. Expdp
- D. DBMS_Cloud package
正解：D
解説：
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.
質問 # 31
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. Automates key modeling steps such as algorithm selection, feature selection, and hyperparameter tuning.
- C. 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.
- D. When creating a notebook from an experiment-produced Model, the top algorithm in the Leader Board is automatically selected and converted to OML4Py code.
正解：A、B
解説：
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
質問 # 32
For which two types of notebooks can you schedule a job? (Choose two.)
- A. Notebooks under Personal templates
- B. Notebooks under Shared templates
- C. Notebooks shared with you
- D. Notebooks owned by you
正解：C、D
解説：
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.
質問 # 33
You are working as an application developer using Oracle Machine Learning Notebooks and want to get your project and notebooks reviewed by a subject matter expert (SME). You granted the Developer permission to the SME on the workspace. Which two actions can be performed by the SME? (Choose two.)
- A. View, create, run, and update any notebook in the workspace.
- B. Create new projects.
- C. Create jobs for shared notebooks.
- D. View and run jobs of shared notebooks.
- E. Create new workspaces.
正解：A、C
解説：
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/grant-workspace-permissions
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/workspace-permissions.html
質問 # 34
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.
正解：C、D、E
解説：
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/
質問 # 35
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. Minimum Failure Allowed
- B. Maximum Number of Runs
- C. Maximum Failure Allowed
- D. Timeout in Minutes
正解：C
解説：
Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/get-started-jobs.html#GUID-
質問 # 36
Which type of machine learning algorithm is used to deal with noise in incoming data?
- A. Classification
- B. Regression
- C. Clustering
- D. Dimensionality Reduction
正解：D
解説：
Explanation
https://blogs.oracle.com/machinelearning/post/using-svd-for-dimensionality-reduction
質問 # 37
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 includes parallelized in-database algorithms.
- E. It provides a development environment to build models and score data.
- F. It enables data analytics, data discovery, and data visualizations.
正解：B、D、E、F
解説：
Explanation
https://docs.oracle.com/en/cloud/paas/autonomous-database/adbsa/autonomous-oml.html#GUID-63F2D68B-6D
質問 # 38
......
Oracle 1z0-1096-23 認定試験の出題範囲：
| トピック | 出題範囲 |
|---|---|
| トピック 1 |
|
| トピック 2 |
|
| トピック 3 |
|
| トピック 4 |
|
| トピック 5 |
|
| トピック 6 |
|
| トピック 7 |
|
| トピック 8 |
|
Oracle Database 1z0-1096-23試験練習問題集：https://jp.fast2test.com/1z0-1096-23-premium-file.html