Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 497 · 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.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
2. 2.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
3. 3.Which of these is bad for training a model? (a) checking labels twice (b) photos in many lights (c) correct labels (d) blurry, unclear photos
4. 4.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
5. 5.🔍 Which is the odd one out? (a) photos in many lights (b) very few examples (c) new data for testing (d) examples of every type
6. 6.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
7. 7.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
8. 8.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
10. 10.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
11. 11.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
12. 12.🔍 Which is the odd one out? (a) only one kind of example (b) labels added at random (c) examples of every type (d) copies of one photo
13. 13.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
14. 14.🏷️ 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
15. 15.Which of these is bad for training a model? (a) correct labels (b) photos in many lights (c) copies of one photo (d) checking labels twice
16. 16.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
17. 17.True or false: “copies of one photo” is good for training a model. (a) True (b) False
18. 18.🏷️ 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
19. 19.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
20. 20.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
21. 21.🏷️ 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
22. 22.🔍 Which is the odd one out? (a) wrong labels (b) correct labels (c) testing on training data (d) very few examples
23. 23.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a list of rules only (c) one single photo (d) a song about dogs
24. 24.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
25. 25.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
26. 26.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) examples of every type (b) checking labels twice (c) copies of one photo (d) many varied examples
28. 28.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
29. 29.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
30. 30.Which of these is bad for training a model? (a) correct labels (b) many varied examples (c) checking labels twice (d) labels added at random
31. 31.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
32. 32.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
33. 33.True or false: “wrong labels” is good for training a model. (a) True (b) False
34. 34.🔍 Which is the odd one out? (a) blurry, unclear photos (b) wrong labels (c) new data for testing (d) only one kind of example
35. 35.True or false: “photos in many lights” is good for training a model. (a) False (b) True
36. 36.🔍 Which is the odd one out? (a) testing on training data (b) very few examples (c) wrong labels (d) checking labels twice
37. 37.🔍 Which is the odd one out? (a) wrong labels (b) examples of every type (c) clear, sharp examples (d) photos in many lights
38. 38.True or false: “correct labels” is good for training a model. (a) False (b) True
39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
40. 40.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will shut down (c) it will turn yellow (d) it will be perfect

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