Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 352 · 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.Which of these is bad for training a model? (a) examples of every type (b) photos in many lights (c) many varied examples (d) only one kind of example
2. 2.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
3. 3.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) many labelled photos (d) a song about dogs
4. 4.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
5. 5.True or false: “correct labels” is bad for training a model. (a) True (b) False
6. 6.Which of these is good for training a model? (a) labels added at random (b) only one kind of example (c) testing on training data (d) new data for testing
7. 7.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
9. 9.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
10. 10.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
11. 11.🧠 Machine learning is a way for computers to… (a) learn from data (b) print pages (c) charge faster (d) clean screens
12. 12.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
13. 13.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it may get it wrong (c) it will shut down (d) it will turn yellow
14. 14.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) change colour (d) better at its task
15. 15.🔍 Which is the odd one out? (a) new data for testing (b) blurry, unclear photos (c) clear, sharp examples (d) photos in many lights
16. 16.🏷️ 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
17. 17.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
18. 18.Which of these is good for training a model? (a) many varied examples (b) labels added at random (c) very few examples (d) wrong labels
19. 19.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
20. 20.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
21. 21.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) very few examples (d) clear, sharp examples
22. 22.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
23. 23.Which of these is bad for training a model? (a) many varied examples (b) correct labels (c) checking labels twice (d) copies of one photo
24. 24.Which of these is bad for training a model? (a) correct labels (b) many varied examples (c) testing on training data (d) examples of every type
25. 25.🏷️ What is a “label” in machine learning? (a) the price (b) the right answer tag (c) the font size (d) a sticker on a laptop
26. 26.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) many varied examples (b) wrong labels (c) correct labels (d) photos in many lights
28. 28.True or false: “many varied examples” is bad for training a model. (a) True (b) False
29. 29.True or false: “very few examples” is bad for training a model. (a) False (b) True
30. 30.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
31. 31.True or false: “wrong labels” is good for training a model. (a) False (b) True
32. 32.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
33. 33.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
34. 34.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
35. 35.True or false: “very few examples” is good for training a model. (a) True (b) False
36. 36.🏷️ 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
37. 37.True or false: “new data for testing” is good for training a model. (a) False (b) True
38. 38.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
39. 39.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
40. 40.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True

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