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Oracle Machine Learning using Autonomous Database 2022 Specialist Sample Questions:

1. Which is a FALSE statement regarding Oracle Machine Learning (OML)?

A) OML provides scalable statistical functions though OML4Py and OML4R.
B) OML provides integration with open source Python and R statistical analysis functions.
C) OML offerings need a separate data visualization tool for creating visualization.
D) OML provides univariate and multivariate statistics.

2. Which feature of Oracle Machine Learning Notebooks should you use for data analysis, data discovery, data visualization, and collaboration on Oracle Autonomous Database?

A) Project
B) Job
C) Notebook
D) Workspace

3. 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) One-Class Support Vector Machine
B) Explicit Semantic Analysis
C) Support Vector Machine (Regression)
D) Generalized Linear Model (Regression)
E) Neural Networks (Regression)
F) Generalized Linear Model (Classification)

4. Which task is NOT required by an Administrator when adding a new user to Oracle Machine Leamina (OML) Notebooks?

A) Issue grant commands on the database to allow access to the tables associated with the user's Oracle Machine Learning Notebooks.
B) Provide the user with an Autonomous Data Warehouse client wallet for remote authentication.
C) Add the user's full name and email ID in the Oracle Machine Learning Management User Interface.
D) Create an OML username and password for the user in the Oracle Machine Learning Management User Interface.

5. 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 selection, Algorithm selection
D) Model tuning. Algorithm selection. Feature selection

Solutions: