Machine Learning for Kids Worksheet

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

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