Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 106 · 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 good for training a model. (a) True (b) False
2. 2.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
3. 3.🏷️ 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
4. 4.🏷️ 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
5. 5.True or false: “photos in many lights” is good for training a model. (a) True (b) False
6. 6.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) correct labels (d) blurry, unclear photos
7. 7.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
8. 8.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
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) not spam (b) spam
10. 10.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) many labelled photos (c) one single photo (d) a song about dogs
11. 11.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
12. 12.Which of these is good for training a model? (a) copies of one photo (b) examples of every type (c) blurry, unclear photos (d) testing on training data
13. 13.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) examples of every type (d) very few examples
14. 14.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
15. 15.True or false: “testing on training data” is bad for training a model. (a) False (b) True
16. 16.🔍 Which is the odd one out? (a) only one kind of example (b) testing on training data (c) examples of every type (d) labels added at random
17. 17.True or false: “testing on training data” is good for training a model. (a) False (b) True
18. 18.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
19. 19.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) forget everything (d) slower to switch on
20. 20.Which of these is bad for training a model? (a) clear, sharp examples (b) many varied examples (c) new data for testing (d) labels added at random
21. 21.🔍 Which is the odd one out? (a) photos in many lights (b) labels added at random (c) only one kind of example (d) blurry, unclear photos
22. 22.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will be perfect (c) it will shut down (d) it may get it wrong
23. 23.🔍 Which is the odd one out? (a) examples of every type (b) many varied examples (c) wrong labels (d) photos in many lights
24. 24.🏷️ 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
25. 25.🔍 Which is the odd one out? (a) new data for testing (b) copies of one photo (c) very few examples (d) blurry, unclear photos
26. 26.🔍 Which is the odd one out? (a) labels added at random (b) examples of every type (c) checking labels twice (d) correct labels
27. 27.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
28. 28.🔍 Which is the odd one out? (a) only one kind of example (b) copies of one photo (c) checking labels twice (d) wrong labels
29. 29.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
30. 30.🔍 Which is the odd one out? (a) correct labels (b) only one kind of example (c) wrong labels (d) very few examples
31. 31.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) checking labels twice (d) copies of one photo
32. 32.Which of these is good for training a model? (a) very few examples (b) only one kind of example (c) checking labels twice (d) copies of one photo
33. 33.🧠 Machine learning is a way for computers to… (a) learn from data (b) print pages (c) clean screens (d) charge faster
34. 34.True or false: “new data for testing” is good for training a model. (a) False (b) True
35. 35.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
36. 36.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
37. 37.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
38. 38.True or false: “labels added at random” is good for training a model. (a) False (b) True
39. 39.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
40. 40.Which of these is bad for training a model? (a) clear, sharp examples (b) testing on training data (c) checking labels twice (d) many varied examples

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