Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 447 · 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: “labels added at random” is bad for training a model. (a) True (b) False
2. 2.🏷️ 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
3. 3.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
4. 4.Which of these is good for training a model? (a) copies of one photo (b) checking labels twice (c) only one kind of example (d) testing on training data
5. 5.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
6. 6.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
7. 7.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
9. 9.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
10. 10.Which of these is good for training a model? (a) copies of one photo (b) very few examples (c) photos in many lights (d) only one kind of example
11. 11.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
12. 12.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) the right answer tag (d) a sticker on a laptop
13. 13.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
14. 14.Which of these is good for training a model? (a) copies of one photo (b) very few examples (c) new data for testing (d) wrong labels
15. 15.True or false: “examples of every type” is bad for training a model. (a) False (b) True
16. 16.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
17. 17.True or false: “labels added at random” is good for training a model. (a) False (b) True
18. 18.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) better at its task (d) forget everything
19. 19.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
20. 20.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
21. 21.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will turn yellow (c) it will be perfect (d) it will shut down
22. 22.🏷️ 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) not spam (b) spam
23. 23.Which of these is good for training a model? (a) only one kind of example (b) labels added at random (c) many varied examples (d) wrong labels
24. 24.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
25. 25.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) one single photo (d) a list of rules only
26. 26.🔍 Which is the odd one out? (a) copies of one photo (b) many varied examples (c) examples of every type (d) new data for testing
27. 27.Which of these is bad for training a model? (a) examples of every type (b) testing on training data (c) new data for testing (d) photos in many lights
28. 28.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
29. 29.True or false: “testing on training data” is bad for training a model. (a) True (b) False
30. 30.🔍 Which is the odd one out? (a) photos in many lights (b) examples of every type (c) blurry, unclear photos (d) clear, sharp examples
31. 31.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
32. 32.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
33. 33.True or false: “new data for testing” is good for training a model. (a) False (b) True
34. 34.True or false: “checking labels twice” is good for training a model. (a) True (b) False
35. 35.🔍 Which is the odd one out? (a) very few examples (b) many varied examples (c) correct labels (d) checking labels twice
36. 36.🏷️ 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
37. 37.Which of these is bad for training a model? (a) many varied examples (b) blurry, unclear photos (c) checking labels twice (d) new data for testing
38. 38.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
39. 39.True or false: “only one kind of example” is good for training a model. (a) False (b) True
40. 40.Which of these is bad for training a model? (a) correct labels (b) checking labels twice (c) only one kind of example (d) photos in many lights

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