WorksheetsQuiz AI - Classification and AI Lab
Total questions: 30
Worksheet time: 15mins
What is the main goal of Artificial Intelligence (AI)?
To make computers think and learn like humans
To play video games
To only store information
To draw pictures
Which type of AI learns from labeled data?
Supervised Learning
Unsupervised Learning
Random Learning
Free Learning
Which type of AI groups data without labels?
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Assisted Learning
In AI, what is a “feature”?
The answer the AI gives
The question asked by the user
A piece of data used to make a decision
A mistake in the model
What is a “model” in AI?
A drawing of data
A set of rules created from training data
A human who explains AI
A type of computer
What do we call the information used to train an AI?
Labels
Data
Predictions
Features
Which of these is an example of supervised learning?
Sorting clothes by color without labels
Learning to recognize cats using pictures with “cat” or “not cat” labels
Playing a video game by trial and error
Guessing without feedback
Why is testing important in AI?
To make the AI slower
To see if the model works correctly
To create more features
To delete wrong data
Which of these is an example of a feature for a fruit?
“Fruit” or “Vegetable”
Sweetness
Prediction
Model
What is a “label” in AI?
The brand of the dataset
The category we want to predict
The graph of the data
The answer key
What does “classification” mean?
Predicting a number
Predicting a category
Deleting data
Mixing data randomly
What kind of data can be separated into groups?
Continuous data
Categorical data
Random data
Infinite data
In the fruit and veggie activity, which two features were used?
Color and size
Sweetness and easy to eat
Weight and price
Smell and temperature
What happens if a test point is on the line in the graph?
The model ignores it
The model must still decide
The model always calls it a fruit
The model always calls it a vegetable
What is a real-life problem with misclassification?
It wastes paper
It can give wrong decisions about people
It makes food taste bad
It slows computers
Why is testing models important?
To see if the computer can draw graphs
To check if the decisions are correct
To collect more food data
To delete bad features
What happens if we try to classify ice cream and chips with the fruit/veggie model?
It works perfectly
The model makes silly mistakes
The AI becomes faster
The AI refuses to answer
When we place foods on a graph with sweetness on the X-axis and easy to eat on the Y-axis, what does each point represent?
A student in the class
A single fruit or vegetable
The line that separates groups
The answer key for the model
Why do we draw a line on the X/Y graph when classifying fruits and vegetables?
To make the graph look pretty
To separate the data into two groups
To erase mistakes on the graph
To add more fruits and veggies
What can happen if a food point is very close to the line on the graph?
The model may have a hard time deciding its category
The food disappears from the graph
The computer automatically chooses “vegetable”
The data becomes wrong and useless
What tool was introduced in Lesson 6?
Data Studio
AI Lab
Graph Maker
Math Explorer
What is the purpose of using machine learning to make recommendations?
To help people choose things they might like
To delete data from the computer
To create colorful shapes
To make the computer faster
In AI Lab, what was the first fun challenge students tried?
Sorting fruits in the kitchen
Teaching the computer to recognize shapes
Drawing their favorite food
Writing a story about AI
Which of these is an example of a feature for shapes?
Number of sides
Name of the student
Day of the week
Teacher’s name
Why did AI Bot get confused with some shapes?
Too many features without strong relationships
Not enough colors
Students clicked the wrong button
Shapes disappeared
What is important when choosing features for a model?
Use as many features as possible
Only choose features with strong relationships
Always use color only
Pick features randomly
What accuracy did students need with the pizza data?
50%
70%
80%
100%
What role do humans play in AI Lab?
Nothing, the computer does everything
Choosing data and features
Deleting mistakes only
Coloring shapes
What happens if you train a model with all features?
It always gets 100% accuracy
Sometimes it becomes less accurate
It breaks the AI Lab
It predicts the future
What kind of problem did students solve with restaurant data?
Guessing fruit names
Making food recipes
Creating recommendations
Drawing graphs by hand
