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WorksheetsFinal exam Semester 1 - 12B - Jana
Total questions: 25
Worksheet time: 13mins
What is the main goal of Artificial Intelligence (AI)?
To store large amounts of data
To help machines think and make decisions like humans
To make computers larger and faster
To reduce the number of computer programs needed
Machine learning allows a computer to:
Memorize all previous data without finding patterns
Learn from data and make predictions or decisions
Write code by itself
Always make perfect decisions without errors
A “dataset” is:
A type of computer program
A collection of data used for training or testing a model
A graph of numbers only
A way to speed up the internet
A “feature” in machine learning is:
A characteristic or value used to make predictions
The final prediction of the model
A type of computer algorithm
The number of students in a class
A “label” in machine learning is:
The name of the dataset
The value or category the model is trying to predict
A type of algorithm
A feature used in training
Supervised learning is when:
The model learns from labeled data
The model explores patterns without labels
The model guesses randomly
The model predicts numbers only
Unsupervised learning is when:
The model learns from labeled data
The model learns patterns in data without labels
The model predicts outcomes for humans
The model is trained only on images
Classification models are used to:
Predict numerical values
Separate data into groups or categories
Delete unnecessary features
Measure internet speed
Which of these is an example of a classification task?
Predicting the number of apples in a basket
Deciding whether a photo shows a cat or a dog
Calculating the total price of items in a cart
Measuring the temperature outside
During training, a model:
Learns patterns in the training data
Tests itself on new data
Always produces random outputs
Deletes old features
Testing a model is done to:
Train it further
Check how accurate it is on new data
Remove bias
Increase the number of features
Bias in a model occurs when:
The model always predicts correctly
The model makes unfair predictions because of unbalanced or incomplete data
The model uses too many features
The dataset is too large
Which of these is an example of a supervised learning task?
Sorting a list of numbers
Predicting whether an email is spam or not spam using labeled examples
Randomly guessing the next number in a sequence
Grouping data points without labels
Which of these is an example of unsupervised learning?
Predicting house prices based on past sales
Grouping customers by purchasing behavior without knowing their age
Classifying emails as spam or not spam
Training a model on labeled images
Patterns in data help models to:
Memorize the dataset only
Make predictions or decisions based on previous examples
Generate random numbers
Delete unnecessary features automatically
Why do we need multiple features in a dataset?
To confuse the model
To give the model more information to make accurate predictions
To increase the file size
To make the model slower
What is the purpose of labeling data?
To organize files on a computer
To provide correct answers for the model to learn from
To increase the number of features
To make the data invisible
Which of the following is an example of AI helping people in real life?
A robot that automatically sorts emails
An app that helps visually impaired people identify objects
A computer playing chess
All of the above
A good dataset for training a model should be:
Small and incomplete
Large, diverse, and representative of real-world scenarios
Randomly generated with no relation to the problem
Made only of one type of example
Evaluating a model helps to:
Improve its accuracy and detect any bias
Make the dataset bigger
Automatically create new features
Replace human decision-making completely
What does “AI” stand for?
Automatic Internet
Artificial Intelligence
Assisted Input
Advanced Information
What is an example of a real-world application of AI/ML?
Recognizing images or objects (e.g. identifying fish or faces)
Hand-writing letters on paper
Only playing video games
Doing homework without any input
Which of the following is NOT a goal of AI?
Learning from experience
Understanding language
Growing crops
Problem-solving
Amazon’s “customers also bought” feature is:
Chatbot
Virtual assistant
Recommendation system
Finance AI
Detecting fraud in credit card use is an example of:
Education AI
Finance AI
Healthcare AI
Navigation AI
