Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 149 · 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 is the odd one out? (a) very few examples (b) clear, sharp examples (c) testing on training data (d) copies of one photo
2. 2.Which of these is bad for training a model? (a) checking labels twice (b) wrong labels (c) many varied examples (d) new data for testing
3. 3.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) slower to switch on (d) forget everything
4. 4.Which of these is good for training a model? (a) copies of one photo (b) blurry, unclear photos (c) labels added at random (d) correct labels
5. 5.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
6. 6.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
7. 7.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) a song about dogs (c) many labelled photos (d) one single photo
8. 8.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
9. 9.🔍 Which is the odd one out? (a) clear, sharp examples (b) only one kind of example (c) photos in many lights (d) correct labels
10. 10.🔍 Which is the odd one out? (a) wrong labels (b) many varied examples (c) only one kind of example (d) blurry, unclear photos
11. 11.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
12. 12.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
13. 13.🏷️ 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
14. 14.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will shut down (c) it may get it wrong (d) it will turn yellow
15. 15.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) photos in many lights (d) blurry, unclear photos
16. 16.True or false: “very few examples” is bad for training a model. (a) False (b) True
17. 17.🔍 Which is the odd one out? (a) photos in many lights (b) copies of one photo (c) new data for testing (d) correct labels
18. 18.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
19. 19.🏷️ 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
20. 20.🔍 Which is the odd one out? (a) blurry, unclear photos (b) labels added at random (c) very few examples (d) examples of every type
21. 21.🏷️ What is a “label” in machine learning? (a) the font size (b) a sticker on a laptop (c) the right answer tag (d) the price
22. 22.🔍 Which is the odd one out? (a) correct labels (b) clear, sharp examples (c) new data for testing (d) labels added at random
23. 23.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
24. 24.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
25. 25.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
26. 26.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
27. 27.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
28. 28.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
29. 29.Which of these is good for training a model? (a) new data for testing (b) copies of one photo (c) testing on training data (d) wrong labels
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
31. 31.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
32. 32.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
33. 33.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
34. 34.Which of these is good for training a model? (a) testing on training data (b) labels added at random (c) photos in many lights (d) copies of one photo
35. 35.Which of these is bad for training a model? (a) testing on training data (b) new data for testing (c) correct labels (d) many varied examples
36. 36.🔍 Which is the odd one out? (a) new data for testing (b) clear, sharp examples (c) examples of every type (d) wrong labels
37. 37.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
38. 38.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) very few examples (d) new data for testing
39. 39.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
40. 40.Which of these is bad for training a model? (a) examples of every type (b) clear, sharp examples (c) photos in many lights (d) copies of one photo

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