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Oracle 1z0-1096-22 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Model Building and Evaluation | - Applying machine learning algorithms in Autonomous Database - Model evaluation and performance metrics |
| Topic 2: Data Preparation and Exploration | - Feature selection and data preprocessing techniques - Data loading and transformation using SQL and Oracle tools |
| Topic 3: Oracle Machine Learning Notebooks | - Using OML Notebooks for data science workflows - SQL and Python integration in OML |
| Topic 4: Introduction to Oracle Machine Learning and Autonomous Database | - Oracle Autonomous Database architecture overview - Machine learning capabilities in Autonomous Database |
| Topic 5: Model Deployment and Management | - Model lifecycle management and monitoring - Deploying machine learning models in Oracle Autonomous Database |
Oracle Machine Learning using Autonomous Database 2022 Specialist Sample Questions:
1. Which three actions can be performed by an Administrator in Oracle Machine Learning (OML) Notebooks?
A) Reassign workspaces to users.
B) View notebooks.
C) Create, edit and delete OML users.
D) Create, run and delete notebooks.
E) Create and run jobs.
2. Which two are required by an administrator while adding a new user to Oracle Machine Learning (OML) Notebooks?
A) OML username and password
B) User's name and email ID
C) Privileges to be provided
D) Wallet information to connect to ADB
E) Autonomous Database (ADB) name
3. Which three services can be used to access Oracle Machine Learning Notebooks? (Choose three.)
A) Autonomous Data Warehouse
B) Autonomous Transaction Processing
C) Oracle Application Express
D) Autonomous Dedicated Infrastructure
E) Autonomous JSON Database
4. 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
5. You want to segment your customer data for groups to build supervised models.
What should you use to achieve this?
A) Classification
B) Clustering
C) Feature Extraction
D) Regression
Solutions:
| Question # 1 Answer: B,C,E | Question # 2 Answer: A,B | Question # 3 Answer: A,B,E | Question # 4 Answer: A | Question # 5 Answer: D |
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