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Oracle 1z0-1096-22 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Preparation and Exploration | 20% | - Data access and transformation
|
| Administration and Security | 10% | - Access control and privileges
|
| OML Notebooks and Environment | 15% | - Workspace and notebook management
|
| Oracle Machine Learning Fundamentals | 15% | - Machine learning concepts and paradigms
|
| Building and Evaluating Models | 25% | - Model development and validation
|
| AutoML and Model Management | 15% | - Automated machine learning
|
Oracle Machine Learning using Autonomous Database 2022 Specialist Sample Questions:
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. Neural Networks (Regression)
- C. One-Class Support Vector Machine
- D. Generalized Linear Model (Classification)
- E. Support Vector Machine (Regression)
- F. Generalized Linear Model (Regression)
Correct Answer: A,C,F 🗳️
Which three types of forms are available in Oracle Machine Learning Notebooks?
- A. Text Input form
- B. List form
- C. Check Box form
- D. Select form
- E. Radio form
Correct Answer: A,C,D 🗳️
Which type of machine learning algorithm is used to deal with noise in incoming data?
- A. Clustering
- B. Dimensionality Reduction
- C. Regression
- D. Classification
Correct Answer: B 🗳️
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What is the proper workflow for analyzing data in Oracle Machine Learning?
- A. Prepare the data, build the model, evaluate the model, and deploy the model.
- B. Build the model, prepare the data, evaluate the model, and deploy the model.
- C. Evaluate the model, prepare the data, build the model, and deploy the model.
- D. Get predictions from the model, prepare the data, build the model, and deploy the model
Correct Answer: B 🗳️
Which three are supervised machine learning algorithms?
- A. K-means clustering
- B. Random Forest
- C. Association rule
- D. Support Vector Machines
- E. Linear Regression
Correct Answer: B,D,E 🗳️
