Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 58 · 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 may get it wrong (b) it will be perfect (c) it will shut down (d) it will turn yellow
2. 2.True or false: “examples of every type” is bad for training a model. (a) False (b) True
3. 3.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) new data for testing (d) testing on training data
4. 4.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
5. 5.🏷️ 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
6. 6.🔍 Which is the odd one out? (a) clear, sharp examples (b) labels added at random (c) testing on training data (d) very few examples
7. 7.🏷️ 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
8. 8.True or false: “very few examples” is bad for training a model. (a) True (b) False
9. 9.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
10. 10.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
11. 11.Which of these is good for training a model? (a) wrong labels (b) copies of one photo (c) very few examples (d) correct labels
12. 12.Which of these is bad for training a model? (a) examples of every type (b) copies of one photo (c) many varied examples (d) new data for testing
13. 13.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
14. 14.Which of these is good for training a model? (a) testing on training data (b) checking labels twice (c) copies of one photo (d) only one kind of example
15. 15.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
17. 17.Which of these is bad for training a model? (a) wrong labels (b) clear, sharp examples (c) correct labels (d) examples of every type
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: “wrong labels” is bad for training a model. (a) True (b) False
20. 20.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
21. 21.True or false: “only one kind of example” is good 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 “not spam”. (a) False (b) True
23. 23.🔍 Which is the odd one out? (a) wrong labels (b) testing on training data (c) labels added at random (d) examples of every type
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? “Science project groups are on the board” (a) not spam (b) spam
26. 26.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
27. 27.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
28. 28.📚 Usually, more good examples make a model… (a) forget everything (b) better at its task (c) slower to switch on (d) change colour
29. 29.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
30. 30.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) only one kind of example (d) photos in many lights
31. 31.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
32. 32.🐶 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
33. 33.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
34. 34.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
35. 35.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
36. 36.🔍 Which is the odd one out? (a) very few examples (b) many varied examples (c) copies of one photo (d) labels added at random
37. 37.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
38. 38.True or false: “correct labels” is bad for training a model. (a) False (b) True
39. 39.🔍 Which is the odd one out? (a) very few examples (b) checking labels twice (c) wrong labels (d) only one kind of example
40. 40.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) the right answer tag (d) a sticker on a laptop

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