01
True or false
1 point
True or false: In a dataset, a feature may be numerical, such as size, or categorical, such as neighborhood.
Free Practice Quiz Question List
1 Introduction to Machine Learning and Datasets Online Quiz Questions
Use this free practice quiz with 20 questions to review 1 Introduction to Machine Learning and Datasets, test your knowledge, and prepare for your next test or exam.
20 questions
02
True or false
1 point
True or false: Machine-learning datasets can include images and audio, not just numbers and categories.
- A
True
- B
False
03
Choose one
1 point
A developer trains a model on emails labeled “spam” or “not spam” and wants it to assign one of those categories to a new email. Which type of problem is this?
- A
Regression
- B
Classification
- C
Clustering
04
Choose one
1 point
A model uses past weather examples to predict tomorrow’s temperature as a numerical value. Which type of machine-learning problem is this?
- A
Regression
- B
Classification
- C
Clustering
05
Written response
1 point
In supervised learning, what is the term for the value a model is meant to predict?
06
Fill in the blank
1 point
In a common tabular dataset, each row is one , and each column records a of that example.
07
Written response
1 point
In the housing dataset, how many listed homes are in the North neighborhood?
08
Choose all
1 point
Which issues can reduce the quality of a dataset before it is used? Select all that apply.
- A
Some values are missing
- B
Some examples are duplicated
- C
The dataset contains many columns
- D
Some entries are incorrect
09
Choose all
1 point
Which statements describe how machine learning builds a model? Select all that apply.
- A
A developer provides data and chooses a learning method.
- B
A developer must specify every rule the program will use.
- C
The resulting model captures patterns that can be applied to new examples.
- D
The model can be built without examples or data.
10
Fill in the blank
1 point
In supervised learning, the set of examples with features and known targets that a model uses to learn patterns is called the .
11
Choose one
1 point
A team wants to check how well its trained model predicts on examples it has not learned from. Which dataset should it use?
- A
A set used to teach the model using known targets
- B
A collection of examples grouped without labels
- C
A held-back set used to assess predictions on examples not used for training
12
Choose one
1 point
A housing model is meant to predict whether a home sold above $350,000, rather than predict its exact sale price. Which problem type fits this target?
- A
Regression, because the original dataset contains sale prices
- B
Classification, because the target is a category
- C
Clustering, because the model predicts a category
13
Open ended
1 point
A store has customer purchasing data but no predefined customer groups or target labels. What kind of machine-learning task could help organize the customers, and why?
14
Written response
1 point
A table contains one row describing each home. What is one row called in dataset terminology?
15
Choose one
1 point
A model uses past home sales to predict the sale price of another home. Which type of machine-learning problem is this?
- A
Classification
- B
Regression
- C
Clustering
16
Choose one
1 point
A housing dataset has columns for size, bedrooms, neighborhood, and sale price. If sale price is the prediction target, what kind of feature is the neighborhood column?
- A
A numerical feature
- B
A target
- C
A categorical feature
17
True or false
1 point
True or false: To make predictions, a machine-learning program must have every rule for every possible input specified by a developer in advance.
- A
True
- B
False
18
Choose one
1 point
A model learns from emails labeled “spam” or “not spam” and assigns one of those labels to a new email. What type of machine-learning problem is it solving?
- A
Classification
- B
Regression
- C
Clustering
19
Written response
1 point
In a supervised-learning dataset, what is the term for the value the model is meant to predict?
20
Choose one
1 point
A store wants to group customers with similar purchasing patterns, but it has no preassigned group labels. Which type of machine-learning task fits this goal?
- A
Regression
- B
Classification
- C
Clustering