Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 46 · 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.🐶 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) many labelled photos (d) one single photo
2. 2.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
3. 3.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) new data for testing (d) testing on training data
4. 4.🏷️ 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
5. 5.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
6. 6.Which of these is bad for training a model? (a) examples of every type (b) very few examples (c) many varied examples (d) clear, sharp examples
7. 7.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
8. 8.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
9. 9.Which of these is bad for training a model? (a) labels added at random (b) checking labels twice (c) new data for testing (d) many varied examples
10. 10.True or false: “only one kind of example” is good for training a model. (a) True (b) False
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.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
13. 13.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will shut down (c) it may get it wrong (d) it will be perfect
14. 14.🔍 Which is the odd one out? (a) testing on training data (b) copies of one photo (c) wrong labels (d) checking labels twice
15. 15.🏷️ 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
16. 16.Which of these is good for training a model? (a) labels added at random (b) many varied examples (c) copies of one photo (d) blurry, unclear photos
17. 17.True or false: “testing on training data” is bad for training a model. (a) True (b) False
18. 18.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
19. 19.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
20. 20.🔍 Which is the odd one out? (a) clear, sharp examples (b) photos in many lights (c) checking labels twice (d) blurry, unclear photos
21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
22. 22.True or false: “examples of every type” is good for training a model. (a) True (b) False
23. 23.Which of these is good for training a model? (a) correct labels (b) wrong labels (c) copies of one photo (d) labels added at random
24. 24.🏷️ 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
25. 25.🏷️ 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
26. 26.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
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: “photos in many lights” is good for training a model. (a) False (b) True
29. 29.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
31. 31.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
32. 32.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) slower to switch on (d) forget everything
33. 33.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
34. 34.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
35. 35.🏷️ 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
36. 36.🏷️ 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
37. 37.🔍 Which is the odd one out? (a) examples of every type (b) clear, sharp examples (c) only one kind of example (d) checking labels twice
38. 38.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
39. 39.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
40. 40.True or false: “wrong labels” is good for training a model. (a) True (b) False

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