Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 347 · 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.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
2. 2.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True
3. 3.🐶 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
4. 4.True or false: “correct labels” is bad for training a model. (a) True (b) False
5. 5.🔍 Which is the odd one out? (a) checking labels twice (b) blurry, unclear photos (c) many varied examples (d) examples of every type
6. 6.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) correct labels (d) wrong labels
7. 7.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
8. 8.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) copies of one photo (d) correct labels
9. 9.🔍 Which is the odd one out? (a) labels added at random (b) examples of every type (c) testing on training data (d) copies of one photo
10. 10.🏷️ 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
11. 11.Which of these is bad for training a model? (a) only one kind of example (b) photos in many lights (c) examples of every type (d) correct labels
12. 12.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
13. 13.True or false: “wrong labels” is good for training a model. (a) True (b) False
14. 14.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
15. 15.🔍 Which is the odd one out? (a) many varied examples (b) examples of every type (c) only one kind of example (d) correct labels
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
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: only one kind of example? (a) good for training (b) bad for training
19. 19.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
20. 20.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
21. 21.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
22. 22.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
23. 23.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
24. 24.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
25. 25.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
26. 26.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
27. 27.Which of these is good for training a model? (a) labels added at random (b) copies of one photo (c) checking labels twice (d) very few examples
28. 28.Which of these is good for training a model? (a) blurry, unclear photos (b) copies of one photo (c) very few examples (d) new data for testing
29. 29.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
30. 30.True or false: “many varied examples” is bad for training a model. (a) False (b) True
31. 31.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will shut down (c) it may get it wrong (d) it will turn yellow
32. 32.Which of these is good for training a model? (a) only one kind of example (b) labels added at random (c) photos in many lights (d) testing on training data
33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
34. 34.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) slower to switch on (d) better at its task
35. 35.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) many varied examples (d) testing on training data
36. 36.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
37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
38. 38.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
39. 39.🔍 Which is the odd one out? (a) clear, sharp examples (b) labels added at random (c) correct labels (d) photos in many lights
40. 40.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training

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