Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 206 · 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.🏷️ 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
2. 2.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it may get it wrong (c) it will shut down (d) it will turn yellow
3. 3.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
4. 4.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
5. 5.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
6. 6.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
7. 7.True or false: “new data for testing” 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? “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) True (b) False
10. 10.🏷️ 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
11. 11.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
12. 12.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
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.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a song about dogs (d) a list of rules only
15. 15.🔍 Which is the odd one out? (a) blurry, unclear photos (b) correct labels (c) very few examples (d) labels added at random
16. 16.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) clear, sharp examples (d) wrong labels
17. 17.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
18. 18.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
19. 19.🏷️ 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
20. 20.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
21. 21.🔍 Which is the odd one out? (a) correct labels (b) only one kind of example (c) examples of every type (d) photos in many lights
22. 22.True or false: “wrong labels” is good for training a model. (a) True (b) False
23. 23.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) checking labels twice (d) labels added at random
24. 24.🔍 Which is the odd one out? (a) wrong labels (b) copies of one photo (c) examples of every type (d) testing on training data
25. 25.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
26. 26.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
27. 27.🏷️ 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
28. 28.Which of these is bad for training a model? (a) new data for testing (b) labels added at random (c) checking labels twice (d) examples of every type
29. 29.🔍 Which is the odd one out? (a) clear, sharp examples (b) photos in many lights (c) correct labels (d) wrong labels
30. 30.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
31. 31.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
32. 32.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
33. 33.Which of these is bad for training a model? (a) clear, sharp examples (b) correct labels (c) testing on training data (d) examples of every type
34. 34.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
35. 35.True or false: “correct labels” is bad for training a model. (a) False (b) True
36. 36.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
37. 37.True or false: “examples of every type” is bad for training a model. (a) True (b) False
38. 38.True or false: “labels added at random” is good for training a model. (a) False (b) True
39. 39.True or false: “photos in many lights” is good for training a model. (a) False (b) True
40. 40.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False

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