Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 361 · 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.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
2. 2.True or false: “checking labels twice” is good for training a model. (a) False (b) True
3. 3.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
4. 4.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
5. 5.🔍 Which is the odd one out? (a) wrong labels (b) only one kind of example (c) new data for testing (d) copies of one photo
6. 6.Which of these is bad for training a model? (a) testing on training data (b) many varied examples (c) photos in many lights (d) new data for testing
7. 7.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
8. 8.🏷️ 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
9. 9.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
10. 10.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) blurry, unclear photos (d) many varied examples
11. 11.True or false: “examples of every type” is bad 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) one single photo (b) a list of rules only (c) many labelled photos (d) a song about dogs
13. 13.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
14. 14.True or false: “correct labels” is bad for training a model. (a) False (b) True
15. 15.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
16. 16.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) checking labels twice (d) wrong labels
17. 17.🏷️ 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
18. 18.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
19. 19.Which of these is bad for training a model? (a) checking labels twice (b) correct labels (c) copies of one photo (d) new data for testing
20. 20.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
21. 21.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
22. 22.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
23. 23.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it will turn yellow (d) it may get it wrong
24. 24.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) blurry, unclear photos (d) checking labels twice
25. 25.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the font size (d) the price
26. 26.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
27. 27.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) change colour (d) better at its task
28. 28.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
29. 29.Which of these is good for training a model? (a) labels added at random (b) copies of one photo (c) wrong labels (d) new data for testing
30. 30.Which of these is bad for training a model? (a) many varied examples (b) photos in many lights (c) correct labels (d) very few examples
31. 31.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) only one kind of example (b) blurry, unclear photos (c) wrong labels (d) clear, sharp examples
33. 33.Which of these is bad for training a model? (a) only one kind of example (b) checking labels twice (c) correct labels (d) many varied examples
34. 34.True or false: “only one kind of example” is good for training a model. (a) False (b) True
35. 35.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
36. 36.🔍 Which is the odd one out? (a) wrong labels (b) labels added at random (c) very few examples (d) examples of every type
37. 37.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
38. 38.Which of these is good for training a model? (a) labels added at random (b) copies of one photo (c) clear, sharp examples (d) wrong labels
39. 39.True or false: “new data for testing” is bad for training a model. (a) False (b) True
40. 40.Which of these is good for training a model? (a) wrong labels (b) copies of one photo (c) testing on training data (d) checking labels twice

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