Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 43 · 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 good for training a model? (a) only one kind of example (b) correct labels (c) blurry, unclear photos (d) very few examples
2. 2.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
3. 3.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
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.🏷️ 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
6. 6.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it may get it wrong (c) it will be perfect (d) it will shut down
7. 7.🏷️ 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
8. 8.🔍 Which is the odd one out? (a) clear, sharp examples (b) only one kind of example (c) new data for testing (d) photos in many lights
9. 9.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) change colour (d) forget everything
10. 10.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
11. 11.True or false: “correct labels” is bad for training a model. (a) True (b) False
12. 12.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
13. 13.Which of these is bad for training a model? (a) photos in many lights (b) many varied examples (c) labels added at random (d) examples of every type
14. 14.True or false: “wrong labels” is good for training a model. (a) True (b) False
15. 15.🔍 Which is the odd one out? (a) many varied examples (b) only one kind of example (c) copies of one photo (d) blurry, unclear photos
16. 16.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
17. 17.🏷️ 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
18. 18.Which of these is bad for training a model? (a) examples of every type (b) new data for testing (c) photos in many lights (d) testing on training data
19. 19.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
20. 20.Which of these is bad for training a model? (a) blurry, unclear photos (b) checking labels twice (c) clear, sharp examples (d) examples of every type
21. 21.True or false: “only one kind of example” is good for training a model. (a) True (b) False
22. 22.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
23. 23.🔍 Which is the odd one out? (a) testing on training data (b) only one kind of example (c) copies of one photo (d) checking labels twice
24. 24.🐶 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
25. 25.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) a sticker on a laptop (d) the right answer tag
26. 26.Which of these is bad for training a model? (a) very few examples (b) many varied examples (c) checking labels twice (d) examples of every type
27. 27.Which of these is bad for training a model? (a) only one kind of example (b) examples of every type (c) photos in many lights (d) many varied examples
28. 28.Which of these is bad for training a model? (a) clear, sharp examples (b) examples of every type (c) copies of one photo (d) many varied examples
29. 29.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) clean screens (d) learn from data
30. 30.🔍 Which is the odd one out? (a) copies of one photo (b) correct labels (c) checking labels twice (d) new data for testing
31. 31.True or false: “new data for testing” is bad for training a model. (a) True (b) False
32. 32.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
33. 33.True or false: “many varied examples” is bad for training a model. (a) True (b) False
34. 34.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) photos in many lights (d) wrong labels
35. 35.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
36. 36.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
37. 37.Which of these is good for training a model? (a) examples of every type (b) blurry, unclear photos (c) very few examples (d) only one kind of example
38. 38.Which of these is good for training a model? (a) blurry, unclear photos (b) only one kind of example (c) wrong labels (d) clear, sharp examples
39. 39.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
40. 40.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False

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