Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 6 · 40 questions

AI tip (Show, label, learn): Machine learning learns patterns from many labelled examples — a label is the right answer tag on each example. Good for training: many varied examples, correct labels, every type the model will meet, and separate new data for testing. Bad for training: very few examples, wrong or random labels, only one kind of example, blurry examples, testing on the training data.

1. 1.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it may get it wrong (d) it will turn yellow
2. 2.Which of these is good for training a model? (a) testing on training data (b) labels added at random (c) wrong labels (d) many varied examples
3. 3.🔍 Which is the odd one out? (a) clear, sharp examples (b) labels added at random (c) very few examples (d) wrong labels
4. 4.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
5. 5.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
6. 6.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) many labelled photos (d) a list of rules only
7. 7.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
9. 9.Which of these is bad for training a model? (a) new data for testing (b) very few examples (c) many varied examples (d) correct labels
10. 10.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
11. 11.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
12. 12.Which of these is good for training a model? (a) labels added at random (b) new data for testing (c) only one kind of example (d) copies of one photo
13. 13.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
14. 14.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
15. 15.🔍 Which is the odd one out? (a) checking labels twice (b) photos in many lights (c) correct labels (d) only one kind of example
16. 16.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
17. 17.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
18. 18.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
19. 19.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
21. 21.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) new data for testing (d) labels added at random
22. 22.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) print pages (d) charge faster
23. 23.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the price (d) the right answer tag
24. 24.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
25. 25.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
26. 26.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
27. 27.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
28. 28.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
29. 29.🔍 Which is the odd one out? (a) checking labels twice (b) correct labels (c) testing on training data (d) clear, sharp examples
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
31. 31.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
32. 32.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) correct labels (d) blurry, unclear photos
33. 33.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) better at its task (d) slower to switch on
34. 34.🔍 Which is the odd one out? (a) only one kind of example (b) wrong labels (c) labels added at random (d) examples of every type
35. 35.🔍 Which is the odd one out? (a) checking labels twice (b) blurry, unclear photos (c) labels added at random (d) copies of one photo
36. 36.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
37. 37.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
38. 38.True or false: “new data for testing” is good for training a model. (a) True (b) False
39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) spam (b) not spam
40. 40.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False

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