Machine Learning for Kids Worksheet

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

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