Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 456 · 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) blurry, unclear photos (b) only one kind of example (c) copies of one photo (d) correct labels
2. 2.True or false: “examples of every type” is bad for training a model. (a) True (b) False
3. 3.🐶 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) a song about dogs (d) many labelled photos
4. 4.True or false: “new data for testing” is bad for training a model. (a) True (b) False
5. 5.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
6. 6.Which of these is bad for training a model? (a) photos in many lights (b) clear, sharp examples (c) labels added at random (d) many varied examples
7. 7.🔍 Which is the odd one out? (a) wrong labels (b) correct labels (c) copies of one photo (d) testing on training data
8. 8.🏷️ 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
9. 9.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
10. 10.🔍 Which is the odd one out? (a) very few examples (b) wrong labels (c) testing on training data (d) checking labels twice
11. 11.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
12. 12.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
13. 13.🏷️ 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
14. 14.Which of these is bad for training a model? (a) clear, sharp examples (b) wrong labels (c) examples of every type (d) many varied examples
15. 15.🔍 Which is the odd one out? (a) correct labels (b) very few examples (c) examples of every type (d) many varied examples
16. 16.🏷️ 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
17. 17.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
18. 18.Which of these is bad for training a model? (a) many varied examples (b) blurry, unclear photos (c) checking labels twice (d) new data for testing
19. 19.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
20. 20.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
21. 21.True or false: “correct labels” is bad for training a model. (a) True (b) False
22. 22.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
23. 23.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) many varied examples (d) only one kind of example
24. 24.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
25. 25.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
26. 26.🔍 Which is the odd one out? (a) examples of every type (b) labels added at random (c) correct labels (d) checking labels twice
27. 27.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
28. 28.True or false: “new data for testing” is good for training a model. (a) True (b) False
29. 29.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will turn yellow (c) it will be perfect (d) it may get it wrong
30. 30.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
31. 31.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
32. 32.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
33. 33.True or false: “many varied examples” is good for training a model. (a) False (b) True
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) spam (b) not spam
35. 35.📚 Usually, more good examples make a model… (a) forget everything (b) change colour (c) slower to switch on (d) better at its task
36. 36.🔍 Which is the odd one out? (a) blurry, unclear photos (b) labels added at random (c) photos in many lights (d) copies of one photo
37. 37.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
38. 38.🔍 Which is the odd one out? (a) testing on training data (b) many varied examples (c) blurry, unclear photos (d) labels added at random
39. 39.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
40. 40.Which of these is bad for training a model? (a) clear, sharp examples (b) new data for testing (c) many varied examples (d) very few examples

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