Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 258 · 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.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
2. 2.True or false: “labels added at random” is bad for training a model. (a) True (b) False
3. 3.🔍 Which is the odd one out? (a) many varied examples (b) new data for testing (c) photos in many lights (d) very few examples
4. 4.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
5. 5.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
6. 6.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
7. 7.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
8. 8.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
10. 10.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
11. 11.True or false: “very few examples” is good for training a model. (a) False (b) True
12. 12.🐶 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
13. 13.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
14. 14.Which of these is bad for training a model? (a) examples of every type (b) new data for testing (c) clear, sharp examples (d) wrong labels
15. 15.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
16. 16.🔍 Which is the odd one out? (a) very few examples (b) testing on training data (c) new data for testing (d) blurry, unclear photos
17. 17.True or false: “labels added at random” is good for training a model. (a) False (b) True
18. 18.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
19. 19.🔍 Which is the odd one out? (a) testing on training data (b) very few examples (c) clear, sharp examples (d) blurry, unclear photos
20. 20.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
21. 21.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
22. 22.🏷️ 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
23. 23.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) labels added at random (d) checking labels twice
24. 24.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) photos in many lights (d) testing on training data
25. 25.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
26. 26.True or false: “many varied examples” is bad for training a model. (a) False (b) True
27. 27.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
28. 28.True or false: “photos in many lights” is good for training a model. (a) False (b) True
29. 29.🏷️ 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
30. 30.True or false: “testing on training data” is bad for training a model. (a) True (b) False
31. 31.True or false: “correct labels” is bad for training a model. (a) False (b) True
32. 32.🔍 Which is the odd one out? (a) examples of every type (b) many varied examples (c) only one kind of example (d) clear, sharp examples
33. 33.Which of these is good for training a model? (a) new data for testing (b) wrong labels (c) only one kind of example (d) copies of one photo
34. 34.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
35. 35.📚 Usually, more good examples make a model… (a) forget everything (b) better at its task (c) slower to switch on (d) change colour
36. 36.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
37. 37.True or false: “only one kind of example” is good for training a model. (a) True (b) False
38. 38.🏷️ 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
39. 39.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
40. 40.🔍 Which is the odd one out? (a) very few examples (b) testing on training data (c) labels added at random (d) photos in many lights

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