Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 205 · 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) very few examples (c) clear, sharp examples (d) blurry, unclear photos
2. 2.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
3. 3.🔍 Which is the odd one out? (a) only one kind of example (b) checking labels twice (c) testing on training data (d) copies of one photo
4. 4.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the font size (c) the price (d) a sticker on a laptop
5. 5.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
6. 6.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
7. 7.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
8. 8.🔍 Which is the odd one out? (a) labels added at random (b) copies of one photo (c) clear, sharp examples (d) blurry, unclear photos
9. 9.Which of these is bad for training a model? (a) very few examples (b) correct labels (c) examples of every type (d) new data for testing
10. 10.🔍 Which is the odd one out? (a) many varied examples (b) photos in many lights (c) new data for testing (d) labels added at random
11. 11.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
12. 12.True or false: “copies of one photo” is good for training a model. (a) False (b) True
13. 13.True or false: “many varied examples” is good for training a model. (a) True (b) False
14. 14.Which of these is bad for training a model? (a) photos in many lights (b) examples of every type (c) many varied examples (d) testing on training data
15. 15.True or false: “labels added at random” is bad for training a model. (a) True (b) False
16. 16.True or false: “only one kind of example” is good for training a model. (a) True (b) False
17. 17.Which of these is good for training a model? (a) testing on training data (b) blurry, unclear photos (c) photos in many lights (d) labels added at random
18. 18.🔍 Which is the odd one out? (a) examples of every type (b) new data for testing (c) very few examples (d) checking labels twice
19. 19.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
20. 20.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) learn from data (d) print pages
21. 21.Which of these is bad for training a model? (a) photos in many lights (b) only one kind of example (c) checking labels twice (d) many varied examples
22. 22.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
23. 23.🔍 Which is the odd one out? (a) very few examples (b) blurry, unclear photos (c) examples of every type (d) labels added at random
24. 24.🔍 Which is the odd one out? (a) labels added at random (b) copies of one photo (c) photos in many lights (d) wrong labels
25. 25.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
26. 26.True or false: “very few examples” is bad for training a model. (a) True (b) False
27. 27.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
28. 28.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) a song about dogs (d) many labelled photos
29. 29.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
30. 30.🏷️ 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
31. 31.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
32. 32.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
33. 33.Which of these is good for training a model? (a) copies of one photo (b) testing on training data (c) correct labels (d) labels added at random
34. 34.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
35. 35.🔍 Which is the odd one out? (a) blurry, unclear photos (b) checking labels twice (c) many varied examples (d) photos in many lights
36. 36.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
37. 37.True or false: “checking labels twice” is good for training a model. (a) True (b) False
38. 38.🔍 Which is the odd one out? (a) blurry, unclear photos (b) labels added at random (c) wrong labels (d) correct labels
39. 39.Which of these is bad for training a model? (a) new data for testing (b) wrong labels (c) many varied examples (d) examples of every type
40. 40.🏷️ 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

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