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WorksheetsUnderstanding AI Systems Quiz
Total questions: 15
Worksheet time: 8mins
What is Machine Learning (ML)?
Giving the computer step-by-step rules
A system that only stores information
A method where computers learn patterns from data
A robot that copies human movement
Which example best represents supervised learning?
Grouping news articles automatically
Using labeled emails to detect spam
Learning by trial and error
Finding hidden patterns in customer data
Unsupervised learning is mainly used for:
Predicting house prices
Translating languages
Playing games like AlphaGo
Grouping unlabeled data into clusters
Reinforcement Learning works by:
Rewards and penalties
Reading large text datasets
Using labeled images
Customer segmentation
Which statement about Deep Learning is TRUE?
It does not require large datasets
It uses multi-layer neural networks
It cannot understand images
It only works for text
When an AI groups customers by purchase behavior, this is:
Unsupervised Learning
NLP
Supervised Learning
Deep Learning
In Model Training, what happens after 'Calculate Error'?
Deploy the model
Collect more data
Validaion
Adjust & Learn - update parameters to reduce error
Model “error” in training refers to:
The difference between prediction and correct answer
A crash in the computer
Missing data
How slow the model runs
Large Language Models (LLMs) are specialized in:
Creating 3D shapes
Driving autonomous cars
Detecting fraud in banks
Understanding and generating human language
The step where a model sees unseen data to check accuracy is called:
Training
Validation
Labeling
Deployment
Computer Vision is used in all of these EXCEPT:
Face recognition to unlock phones
Self-driving cars detecting traffic
Understanding human languages
Quality checks in factories
What are the main components of an AI Model?
Data, Algorithm, Testing, Model
Input, Process, Training, Model
Input, Process, Output, Model
Data, Algorithm, Training, Model
Is deep learning able to do the tasks of machine learning?
Yes
No
Some tasks
The opposite (Machine learning does the tasks of deep learning)
If I create a machine learning model to classify if an image is a cat or dog, is this considered a computer vision application?
Yes
No
The trade-off with model sizes is:
Larger = faster,
Smaller = more accurate
All models perform the same regardless of size
Larger = more capable but slower and expensive, Smaller = faster but limited
Smaller = more powerful, Larger = less capable
