Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 110 · 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: “examples of every type” is good for training a model. (a) False (b) True
2. 2.Which of these is good for training a model? (a) labels added at random (b) copies of one photo (c) blurry, unclear photos (d) correct labels
3. 3.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
4. 4.🏷️ 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
5. 5.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) copies of one photo (d) checking labels twice
6. 6.True or false: “correct labels” is bad for training a model. (a) False (b) True
7. 7.True or false: “new data for testing” is bad for training a model. (a) True (b) False
8. 8.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
9. 9.Which of these is good for training a model? (a) testing on training data (b) checking labels twice (c) only one kind of example (d) blurry, unclear photos
10. 10.🏷️ 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
11. 11.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) photos in many lights (d) labels added at random
12. 12.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
13. 13.🔍 Which is the odd one out? (a) correct labels (b) checking labels twice (c) testing on training data (d) many varied examples
14. 14.True or false: “very few examples” is good for training a model. (a) True (b) False
15. 15.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
16. 16.🔍 Which is the odd one out? (a) correct labels (b) photos in many lights (c) new data for testing (d) wrong labels
17. 17.Which of these is good for training a model? (a) new data for testing (b) only one kind of example (c) labels added at random (d) very few examples
18. 18.Which of these is good for training a model? (a) only one kind of example (b) testing on training data (c) very few examples (d) many varied examples
19. 19.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
20. 20.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) a song about dogs (c) one single photo (d) many labelled photos
21. 21.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
22. 22.🔍 Which is the odd one out? (a) correct labels (b) labels added at random (c) copies of one photo (d) very few examples
23. 23.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
24. 24.Which of these is good for training a model? (a) clear, sharp examples (b) labels added at random (c) blurry, unclear photos (d) copies of one photo
25. 25.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
26. 26.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
27. 27.🏷️ 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
28. 28.True or false: “many varied examples” is good for training a model. (a) False (b) True
29. 29.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) better at its task (d) change colour
30. 30.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
31. 31.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
32. 32.🔍 Which is the odd one out? (a) very few examples (b) testing on training data (c) clear, sharp examples (d) copies of one photo
33. 33.🏷️ 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
34. 34.🏷️ 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
35. 35.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) only one kind of example (d) many varied examples
36. 36.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
37. 37.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
38. 38.True or false: “photos in many lights” is good for training a model. (a) False (b) True
39. 39.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
40. 40.🏷️ 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) not spam (b) spam

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