Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 579 · 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: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
2. 2.🔍 Which is the odd one out? (a) wrong labels (b) many varied examples (c) correct labels (d) photos in many lights
3. 3.True or false: “many varied examples” is good for training a model. (a) False (b) True
4. 4.🏷️ What is a “label” in machine learning? (a) the font size (b) the price (c) the right answer tag (d) a sticker on a laptop
5. 5.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a list of rules only (c) a song about dogs (d) one single photo
6. 6.🔍 Which is the odd one out? (a) checking labels twice (b) only one kind of example (c) blurry, unclear photos (d) testing on training data
7. 7.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
8. 8.Which of these is bad for training a model? (a) photos in many lights (b) clear, sharp examples (c) blurry, unclear photos (d) new data for testing
9. 9.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) many varied examples (d) wrong labels
10. 10.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
11. 11.Which of these is bad for training a model? (a) many varied examples (b) correct labels (c) photos in many lights (d) labels added at random
12. 12.🏷️ 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
13. 13.Which of these is bad for training a model? (a) examples of every type (b) clear, sharp examples (c) new data for testing (d) copies of one photo
14. 14.🏷️ 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
15. 15.True or false: “correct labels” is bad for training a model. (a) True (b) False
16. 16.🔍 Which is the odd one out? (a) examples of every type (b) clear, sharp examples (c) labels added at random (d) checking labels twice
17. 17.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
18. 18.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) slower to switch on (d) forget everything
19. 19.Which of these is good for training a model? (a) examples of every type (b) blurry, unclear photos (c) labels added at random (d) only one kind of example
20. 20.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
21. 21.Which of these is good for training a model? (a) testing on training data (b) wrong labels (c) correct labels (d) very few examples
22. 22.🔍 Which is the odd one out? (a) correct labels (b) labels added at random (c) very few examples (d) wrong labels
23. 23.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) checking labels twice (d) blurry, unclear photos
24. 24.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
25. 25.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
26. 26.🏷️ 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
27. 27.True or false: “new data for testing” is good for training a model. (a) True (b) False
28. 28.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
29. 29.🔍 Which is the odd one out? (a) photos in many lights (b) many varied examples (c) examples of every type (d) testing on training data
30. 30.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
31. 31.🏷️ 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
32. 32.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
33. 33.True or false: “only one kind of example” is good for training a model. (a) True (b) False
34. 34.🏷️ 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
35. 35.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
36. 36.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
37. 37.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
38. 38.True or false: “wrong labels” is bad for training a model. (a) True (b) False
39. 39.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
40. 40.True or false: “new data for testing” is bad for training a model. (a) True (b) False

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