Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 45 · 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.Which of these is bad for training a model? (a) checking labels twice (b) correct labels (c) labels added at random (d) many varied examples
2. 2.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) a song about dogs (d) many labelled photos
3. 3.🔍 Which is the odd one out? (a) labels added at random (b) copies of one photo (c) photos in many lights (d) very few examples
4. 4.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
5. 5.True or false: “photos in many lights” is good for training a model. (a) False (b) True
6. 6.🔍 Which is the odd one out? (a) very few examples (b) only one kind of example (c) many varied examples (d) copies of one photo
7. 7.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
8. 8.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
9. 9.Which of these is bad for training a model? (a) examples of every type (b) many varied examples (c) testing on training data (d) new data for testing
10. 10.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) better at its task (d) change colour
11. 11.True or false: “very few examples” is good for training a model. (a) False (b) True
12. 12.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
13. 13.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
14. 14.True or false: “examples of every type” is good for training a model. (a) False (b) True
15. 15.Which of these is bad for training a model? (a) checking labels twice (b) copies of one photo (c) clear, sharp examples (d) photos in many lights
16. 16.True or false: “wrong labels” is good for training a model. (a) True (b) False
17. 17.🔍 Which is the odd one out? (a) labels added at random (b) examples of every type (c) photos in many lights (d) correct labels
18. 18.🔍 Which is the odd one out? (a) copies of one photo (b) clear, sharp examples (c) checking labels twice (d) new data for testing
19. 19.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
20. 20.True or false: “checking labels twice” is good for training a model. (a) False (b) True
21. 21.True or false: “labels added at random” is good for training a model. (a) True (b) False
22. 22.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
23. 23.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
24. 24.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
25. 25.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
26. 26.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
27. 27.🔍 Which is the odd one out? (a) blurry, unclear photos (b) wrong labels (c) very few examples (d) examples of every type
28. 28.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
29. 29.True or false: “copies of one photo” is good for training a model. (a) True (b) False
30. 30.🏷️ 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
31. 31.Which of these is good for training a model? (a) blurry, unclear photos (b) correct labels (c) testing on training data (d) only one kind of example
32. 32.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
33. 33.🔍 Which is the odd one out? (a) blurry, unclear photos (b) clear, sharp examples (c) wrong labels (d) only one kind of example
34. 34.🏷️ 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
35. 35.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) examples of every type (d) blurry, unclear photos
36. 36.Which of these is good for training a model? (a) testing on training data (b) copies of one photo (c) many varied examples (d) labels added at random
37. 37.🏷️ 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
38. 38.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
39. 39.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
40. 40.🧠 Machine learning is a way for computers to… (a) print pages (b) clean screens (c) learn from data (d) charge faster

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