Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 87 · 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) testing on training data (b) wrong labels (c) clear, sharp examples (d) very few examples
2. 2.🏷️ 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
3. 3.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
4. 4.🔍 Which is the odd one out? (a) very few examples (b) testing on training data (c) new data for testing (d) blurry, unclear photos
5. 5.True or false: “copies of one photo” is good for training a model. (a) True (b) False
6. 6.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
7. 7.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
9. 9.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
10. 10.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) a sticker on a laptop (c) the price (d) the font size
11. 11.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
12. 12.🥭 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
13. 13.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) photos in many lights (d) only one kind of example
14. 14.Which of these is bad for training a model? (a) new data for testing (b) blurry, unclear photos (c) checking labels twice (d) clear, sharp examples
15. 15.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
16. 16.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
17. 17.🔍 Which is the odd one out? (a) clear, sharp examples (b) checking labels twice (c) wrong labels (d) many varied examples
18. 18.True or false: “photos in many lights” is good for training a model. (a) True (b) False
19. 19.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
20. 20.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
21. 21.True or false: “very few examples” is good for training a model. (a) False (b) True
22. 22.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
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.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
25. 25.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
26. 26.🔍 Which is the odd one out? (a) only one kind of example (b) wrong labels (c) correct labels (d) very few examples
27. 27.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
28. 28.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
29. 29.True or false: “many varied examples” is bad for training a model. (a) True (b) False
30. 30.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
31. 31.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
32. 32.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
33. 33.🔍 Which is the odd one out? (a) wrong labels (b) clear, sharp examples (c) copies of one photo (d) blurry, unclear photos
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.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
36. 36.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
37. 37.True or false: “labels added at random” is good for training a model. (a) False (b) True
38. 38.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) new data for testing (d) labels added at random
39. 39.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
40. 40.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) a list of rules only (d) many labelled photos

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