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Oracle 1z0-1096-22 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Administration and Security | - Administration Tasks
|
| Topic 2: AutoML and In-Database Machine Learning | - Automated Machine Learning
|
| Topic 3: Oracle Machine Learning Environment | - Oracle Machine Learning Components
|
| Topic 4: Building and Evaluating Models | - Model Development
|
| Topic 5: Oracle Machine Learning Notebooks | - Notebook Development
|
| Topic 6: Data Preparation and Exploration | - Data Analysis
|
| Topic 7: Oracle Machine Learning Fundamentals | - Machine Learning Concepts
|
Oracle Machine Learning using Autonomous Database 2022 Specialist Sample Questions:
1. Examine the output:
A) SET SQLFORMAT ANSICONSOLE
B) SET SQLFORMAT FIXED
C) SET SQLFORMAT DELIMITED
D) SET SQLFORMAT LOADER
2. 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?
A) Explicit Semantic Analysis
B) Generalized Linear Model (Classification)
C) Support Vector Machine (Regression)
D) Generalized Linear Model (Regression)
E) One-Class Support Vector Machine
F) Neural Networks (Regression)
3. 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) The notebook contains code with syntax errors, which need to be corrected first.
B) The specified job already exists.
C) A developer cannot create jobs for notebooks that are shared.
D) The user requires the Create Job role.
4. What is the correct sequence of creating items in Oracle Machine Learning (OML) Notebooks when setting up a new Autonomous Database instance?
A) Notebook, Job, Project, OML User
B) Job, Project, Workspace, Notebook
C) Workspace, OML User, Notebook, Jobs
D) OML User, Notebook, Job
5. You want to segment your customer data for groups to build supervised models.
What should you use to achieve this?
A) Regression
B) Feature Extraction
C) Classification
D) Clustering
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A,D,E | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: A |
