Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 477 · 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.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
2. 2.Which of these is good for training a model? (a) blurry, unclear photos (b) examples of every type (c) copies of one photo (d) labels added at random
3. 3.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
4. 4.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) only one kind of example (d) photos in many lights
5. 5.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
6. 6.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
7. 7.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
8. 8.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) a sticker on a laptop (d) the price
9. 9.🏷️ 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
10. 10.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) testing on training data (d) photos in many lights
11. 11.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
12. 12.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) correct labels (d) copies of one photo
13. 13.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) copies of one photo (d) examples of every type
14. 14.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
15. 15.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
16. 16.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
17. 17.True or false: “very few examples” is good for training a model. (a) True (b) False
18. 18.Which of these is bad for training a model? (a) new data for testing (b) clear, sharp examples (c) testing on training data (d) many varied examples
19. 19.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
20. 20.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
21. 21.True or false: “copies of one photo” is good for training a model. (a) True (b) False
22. 22.True or false: “wrong labels” is good for training a model. (a) True (b) False
23. 23.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
24. 24.🔍 Which is the odd one out? (a) photos in many lights (b) blurry, unclear photos (c) correct labels (d) checking labels twice
25. 25.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
26. 26.Which of these is good for training a model? (a) clear, sharp examples (b) labels added at random (c) wrong labels (d) very few examples
27. 27.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) checking labels twice (d) wrong labels
28. 28.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a song about dogs (d) a list of rules only
29. 29.🏷️ 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
30. 30.True or false: “new data for testing” is bad for training a model. (a) True (b) False
31. 31.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
32. 32.True or false: “examples of every type” is good for training a model. (a) True (b) False
33. 33.True or false: “testing on training data” is bad for training a model. (a) True (b) False
34. 34.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
35. 35.🔍 Which is the odd one out? (a) clear, sharp examples (b) new data for testing (c) correct labels (d) very few examples
36. 36.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
37. 37.🏷️ 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
38. 38.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
39. 39.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
40. 40.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) blurry, unclear photos (d) new data for testing

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