Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 186 · 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) clear, sharp examples (b) copies of one photo (c) new data for testing (d) correct labels
2. 2.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) forget everything (d) change colour
3. 3.Which of these is bad for training a model? (a) only one kind of example (b) examples of every type (c) clear, sharp examples (d) photos in many lights
4. 4.True or false: “photos in many lights” is good for training a model. (a) True (b) False
5. 5.True or false: “testing on training data” is bad for training a model. (a) False (b) True
6. 6.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
7. 7.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
8. 8.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
9. 9.🔍 Which is the odd one out? (a) correct labels (b) examples of every type (c) blurry, unclear photos (d) many varied examples
10. 10.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
11. 11.True or false: “wrong labels” is good for training a model. (a) False (b) True
12. 12.Which of these is bad for training a model? (a) testing on training data (b) checking labels twice (c) clear, sharp examples (d) many varied examples
13. 13.🔍 Which is the odd one out? (a) clear, sharp examples (b) new data for testing (c) checking labels twice (d) testing on training data
14. 14.True or false: “examples of every type” is bad for training a model. (a) True (b) False
15. 15.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
16. 16.True or false: “very few examples” is bad for training a model. (a) True (b) False
17. 17.True or false: “checking labels twice” is good for training a model. (a) True (b) False
18. 18.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
19. 19.🧠 Machine learning is a way for computers to… (a) clean screens (b) print pages (c) learn from data (d) charge faster
20. 20.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
21. 21.Which of these is good for training a model? (a) wrong labels (b) copies of one photo (c) blurry, unclear photos (d) clear, sharp examples
22. 22.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
23. 23.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
24. 24.🐶 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) many labelled photos (d) a song about dogs
25. 25.🏷️ 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
26. 26.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
27. 27.🏷️ 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
28. 28.🥭 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
29. 29.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
30. 30.Which of these is bad for training a model? (a) correct labels (b) very few examples (c) examples of every type (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.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
33. 33.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
34. 34.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
35. 35.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) many varied examples (d) copies of one photo
36. 36.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
37. 37.Which of these is good for training a model? (a) photos in many lights (b) copies of one photo (c) wrong labels (d) testing on training data
38. 38.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
39. 39.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
40. 40.True or false: “correct labels” is bad for training a model. (a) True (b) False

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