Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 339 · 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: wrong labels? (a) bad for training (b) good for training
2. 2.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) many labelled photos (d) a song about dogs
3. 3.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) examples of every type (d) labels added at random
4. 4.True or false: “checking labels twice” is good for training a model. (a) False (b) True
5. 5.True or false: “examples of every type” is bad for training a model. (a) True (b) False
6. 6.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
7. 7.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
8. 8.🏷️ 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
9. 9.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
10. 10.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
11. 11.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will shut down (c) it will be perfect (d) it may get it wrong
12. 12.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) slower to switch on (d) better at its task
13. 13.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the price (d) the right answer tag
14. 14.True or false: “photos in many lights” is good for training a model. (a) False (b) True
15. 15.🏷️ 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
16. 16.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
17. 17.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
18. 18.True or false: “labels added at random” is bad for training a model. (a) False (b) True
19. 19.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) clear, sharp examples (d) very few examples
20. 20.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
22. 22.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
23. 23.True or false: “correct labels” is bad for training a model. (a) False (b) True
24. 24.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) photos in many lights (d) copies of one photo
25. 25.🔍 Which is the odd one out? (a) only one kind of example (b) copies of one photo (c) wrong labels (d) checking labels twice
26. 26.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
27. 27.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
28. 28.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
29. 29.Which of these is bad for training a model? (a) many varied examples (b) copies of one photo (c) clear, sharp examples (d) checking labels twice
30. 30.True or false: “new data for testing” is bad for training a model. (a) False (b) True
31. 31.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
32. 32.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
33. 33.Which of these is good for training a model? (a) wrong labels (b) examples of every type (c) blurry, unclear photos (d) only one kind of example
34. 34.🔍 Which is the odd one out? (a) new data for testing (b) checking labels twice (c) copies of one photo (d) photos in many lights
35. 35.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) many varied examples (d) very few examples
36. 36.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
37. 37.🔍 Which is the odd one out? (a) photos in many lights (b) very few examples (c) labels added at random (d) blurry, unclear photos
38. 38.True or false: “many varied examples” is bad for training a model. (a) False (b) True
39. 39.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
40. 40.🔍 Which is the odd one out? (a) very few examples (b) examples of every type (c) copies of one photo (d) blurry, unclear photos

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