Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 44 · 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.🏷️ 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
2. 2.True or false: “new data for testing” is good for training a model. (a) False (b) True
3. 3.🏷️ 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
4. 4.Which of these is good for training a model? (a) only one kind of example (b) copies of one photo (c) testing on training data (d) new data for testing
5. 5.Which of these is good for training a model? (a) testing on training data (b) many varied examples (c) very few examples (d) copies of one photo
6. 6.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
7. 7.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) correct labels (d) wrong labels
8. 8.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the price (c) a sticker on a laptop (d) the font size
9. 9.🏷️ 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
10. 10.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
11. 11.🏷️ 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
12. 12.🔍 Which is the odd one out? (a) very few examples (b) testing on training data (c) wrong labels (d) correct labels
13. 13.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
14. 14.Which of these is bad for training a model? (a) correct labels (b) very few examples (c) many varied examples (d) new data for testing
15. 15.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
16. 16.Which of these is good for training a model? (a) copies of one photo (b) clear, sharp examples (c) very few examples (d) blurry, unclear photos
17. 17.Which of these is good for training a model? (a) examples of every type (b) labels added at random (c) wrong labels (d) copies of one photo
18. 18.True or false: “only one kind of example” is good for training a model. (a) True (b) False
19. 19.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
20. 20.🔍 Which is the odd one out? (a) blurry, unclear photos (b) only one kind of example (c) photos in many lights (d) wrong labels
21. 21.True or false: “wrong labels” is good for training a model. (a) False (b) True
22. 22.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) labels added at random (d) photos in many lights
23. 23.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will be perfect (c) it will shut down (d) it may get it wrong
24. 24.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
25. 25.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) forget everything (d) change colour
26. 26.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
27. 27.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
29. 29.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
30. 30.True or false: “photos in many lights” is good for training a model. (a) True (b) False
31. 31.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
32. 32.🔍 Which is the odd one out? (a) correct labels (b) examples of every type (c) many varied examples (d) labels added at random
33. 33.True or false: “very few examples” is bad for training a model. (a) True (b) False
34. 34.Which of these is bad for training a model? (a) testing on training data (b) many varied examples (c) examples of every type (d) photos in many lights
35. 35.🏷️ 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
36. 36.🔍 Which is the odd one out? (a) testing on training data (b) new data for testing (c) labels added at random (d) only one kind of example
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: “examples of every type” is bad for training a model. (a) False (b) True
39. 39.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
40. 40.🏷️ 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

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