Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 263 · 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.True or false: “many varied examples” is bad for training a model. (a) True (b) False
2. 2.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
3. 3.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
4. 4.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) wrong labels (d) correct labels
5. 5.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
6. 6.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
7. 7.Which of these is bad for training a model? (a) many varied examples (b) labels added at random (c) photos in many lights (d) clear, sharp examples
8. 8.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
9. 9.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
10. 10.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
11. 11.True or false: “labels added at random” is bad for training a model. (a) False (b) True
12. 12.🔍 Which is the odd one out? (a) clear, sharp examples (b) labels added at random (c) photos in many lights (d) many varied examples
13. 13.Which of these is bad for training a model? (a) checking labels twice (b) correct labels (c) copies of one photo (d) many varied examples
14. 14.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) clean screens (d) print pages
15. 15.True or false: “very few examples” is bad for training a model. (a) False (b) True
16. 16.🏷️ What is a “label” in machine learning? (a) the font size (b) the price (c) a sticker on a laptop (d) the right answer tag
17. 17.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
18. 18.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
19. 19.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
20. 20.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
21. 21.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) many labelled photos (d) a song about dogs
22. 22.📚 Usually, more good examples make a model… (a) better at its task (b) forget everything (c) slower to switch on (d) change colour
23. 23.Which of these is bad for training a model? (a) correct labels (b) many varied examples (c) blurry, unclear photos (d) examples of every type
24. 24.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
25. 25.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
26. 26.True or false: “new data for testing” is bad for training a model. (a) False (b) True
27. 27.Which of these is good for training a model? (a) very few examples (b) clear, sharp examples (c) blurry, unclear photos (d) wrong labels
28. 28.Which of these is bad for training a model? (a) wrong labels (b) correct labels (c) photos in many lights (d) clear, sharp examples
29. 29.True or false: “examples of every type” is bad for training a model. (a) False (b) True
30. 30.True or false: “testing on training data” is bad for training a model. (a) True (b) False
31. 31.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) copies of one photo (b) correct labels (c) new data for testing (d) photos in many lights
33. 33.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
34. 34.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
35. 35.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
36. 36.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) very few examples (d) photos in many lights
37. 37.🏷️ 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
38. 38.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
39. 39.True or false: “correct labels” is good for training a model. (a) True (b) False
40. 40.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training

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