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Oracle 1z0-1096-22 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Introduction to Oracle Machine Learning and Autonomous Database | - Oracle Autonomous Database architecture overview - Machine learning capabilities in Autonomous Database |
| Topic 2: Data Preparation and Exploration | - Data loading and transformation using SQL and Oracle tools - Feature selection and data preprocessing techniques |
| Topic 3: Model Deployment and Management | - Model lifecycle management and monitoring - Deploying machine learning models in Oracle Autonomous Database |
| Topic 4: Oracle Machine Learning Notebooks | - SQL and Python integration in OML - Using OML Notebooks for data science workflows |
| Topic 5: Model Building and Evaluation | - Model evaluation and performance metrics - Applying machine learning algorithms in Autonomous Database |
Oracle Machine Learning using Autonomous Database 2022 Specialist Sample Questions:
Question 1
Which type of machine learning algorithm is used to deal with noise in incoming data?
A. Dimensionality Reduction
B. Classification
C. Regression
D. Clustering
Question 2
Which three types of forms are available in Oracle Machine Learning Notebooks?
A. Radio form
B. List form
C. Select form
D. Check Box form
E. Text Input form
Question 3
Which step is not required to be performed by an administrator when adding a new user to Oracle Machine Learning (OML) Notebooks?
A. Provide the user with Autonomous Database client wallet for remote credentials.
B. Issue grant commands on tables from other schemas to allow access from shared notebooks.
C. Add the user's name and email ID in the Oracle Machine Learning User Management interface.
D. Create an OML username and password for the user in the Oracle Machine Learning User Management interface.
Question 4
Which type of user has access to the Oracle Machine Learning User Management interface?
A. Administrator
B. Manager
C. Guest
D. Developer
Question 5
What is the correct sequence of function invocations of AutoML API from OML4Py to solve a business problem?
A. Model tuning. Algorithm selection. Feature selection
B. Algorithm selection, Feature selection. Model tuning
C. Model selection, Algorithm selection
D. Model selection, Algorithm selection
Solutions:
| Question 1 Answer: A | Question 2 Answer: C,D,E | Question 3 Answer: A | Question 4 Answer: A | Question 5 Answer: B |

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