🤖 ML Scenarios

Question 1
A system learns to recognize handwritten digits by training on thousands of images labeled with numbers 0–9.
Question 2
A robot plays table tennis and learns through trial and error, receiving feedback when it wins or loses a rally.
Question 3
An e-commerce site automatically groups customers into segments based on their purchase behavior, without predefined categories.
Question 4
A real estate app predicts house prices based on features like square footage, location, and number of bedrooms. Output: $325,000.
Question 5
An email system automatically sorts incoming messages into categories: Spam, Important, or Normal.
Question 6
Netflix groups movies together based on viewing patterns without predefined genre categories.
Question 7
A stock trading algorithm learns from historical trades, receiving rewards when it makes profits and penalties when it loses money.
Question 8
A weather app predicts tomorrow's high temperature. Output: 73.5°F.
Question 9
A medical system analyzes X-rays and classifies bones as either "broken" or "healthy."
Question 10
A music streaming service groups songs by similarity without knowing what the playlists should be called.
Question 11
An autonomous drone learns to navigate through obstacles, receiving penalties when it crashes and rewards when it reaches the destination.
Question 12
A food delivery app estimates how long it will take for pizza to arrive. Output: 23 minutes.
Question 13
A social media platform analyzes posts and labels them as positive, negative, or neutral sentiment.
Question 14
A cybersecurity system discovers unknown threat patterns in network traffic without labeled examples.
Question 15
A chess AI learns by playing thousands of games, receiving feedback on wins, losses, and draws to improve its strategy.
Question 16
A bank uses a model to predict a customer's credit score. Output: 742.
Question 17
An app identifies animals in photos as either a dog, cat, or bird.
Question 18
A retailer groups customers based on shopping behavior without knowing what the groups should be.
Question 19
A smart traffic light system learns to adjust timing by observing whether traffic flow improves or worsens.
Question 20
A fitness app estimates the number of calories in a meal based on a photo. Output: 347 calories.