Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 326 · 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 be perfect (b) it will shut down (c) it will turn yellow (d) it may get it wrong
2. 2.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
3. 3.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) only one kind of example (d) examples of every type
4. 4.Which of these is good for training a model? (a) very few examples (b) wrong labels (c) only one kind of example (d) many varied examples
5. 5.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
6. 6.Which of these is bad for training a model? (a) correct labels (b) photos in many lights (c) many varied examples (d) very few examples
7. 7.Which of these is bad for training a model? (a) clear, sharp examples (b) blurry, unclear photos (c) many varied examples (d) checking labels twice
8. 8.Which of these is good for training a model? (a) copies of one photo (b) blurry, unclear photos (c) only one kind of example (d) examples of every type
9. 9.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
10. 10.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) wrong labels (d) checking labels twice
11. 11.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
12. 12.🔍 Which is the odd one out? (a) labels added at random (b) correct labels (c) checking labels twice (d) many varied examples
13. 13.Which of these is bad for training a model? (a) checking labels twice (b) photos in many lights (c) clear, sharp examples (d) copies of one photo
14. 14.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
15. 15.True or false: “only one kind of example” is good for training a model. (a) True (b) False
16. 16.🔍 Which is the odd one out? (a) testing on training data (b) copies of one photo (c) very few examples (d) photos in many lights
17. 17.Which of these is good for training a model? (a) very few examples (b) correct labels (c) copies of one photo (d) labels added at random
18. 18.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
19. 19.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) clean screens (d) learn from data
20. 20.🔍 Which is the odd one out? (a) examples of every type (b) wrong labels (c) many varied examples (d) photos in many lights
21. 21.🏷️ 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
22. 22.🔍 Which is the odd one out? (a) copies of one photo (b) clear, sharp examples (c) labels added at random (d) testing on training data
23. 23.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
24. 24.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
25. 25.🏷️ 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
26. 26.🔍 Which is the odd one out? (a) new data for testing (b) only one kind of example (c) checking labels twice (d) correct labels
27. 27.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
28. 28.📚 Usually, more good examples make a model… (a) better at its task (b) forget everything (c) slower to switch on (d) change colour
29. 29.🏷️ 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
30. 30.Which of these is bad for training a model? (a) examples of every type (b) labels added at random (c) correct labels (d) checking labels twice
31. 31.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
32. 32.🏷️ 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
33. 33.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
34. 34.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
35. 35.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
36. 36.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
37. 37.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
38. 38.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) one single photo (c) many labelled photos (d) a list of rules only
39. 39.True or false: “new data for testing” is bad for training a model. (a) True (b) False
40. 40.🔍 Which is the odd one out? (a) new data for testing (b) copies of one photo (c) correct labels (d) many varied examples

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