Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 327 · 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.🏷️ 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
2. 2.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
3. 3.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
4. 4.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
5. 5.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
6. 6.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) very few examples (d) photos in many lights
7. 7.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
8. 8.Which of these is good for training a model? (a) clear, sharp examples (b) labels added at random (c) wrong labels (d) copies of one photo
9. 9.🔍 Which is the odd one out? (a) blurry, unclear photos (b) correct labels (c) photos in many lights (d) many varied examples
10. 10.🔍 Which is the odd one out? (a) testing on training data (b) copies of one photo (c) checking labels twice (d) very few examples
11. 11.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a list of rules only (c) a song about dogs (d) one single photo
12. 12.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
13. 13.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) testing on training data (d) examples of every type
14. 14.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
15. 15.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) testing on training data (d) new data for testing
16. 16.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
17. 17.Which of these is bad for training a model? (a) checking labels twice (b) new data for testing (c) wrong labels (d) correct labels
18. 18.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
19. 19.🥭 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
20. 20.🔍 Which is the odd one out? (a) testing on training data (b) very few examples (c) copies of one photo (d) examples of every type
21. 21.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
22. 22.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
23. 23.🔍 Which is the odd one out? (a) very few examples (b) correct labels (c) new data for testing (d) examples of every type
24. 24.True or false: “labels added at random” is good for training a model. (a) False (b) True
25. 25.True or false: “copies of one photo” is good for training a model. (a) True (b) False
26. 26.🔍 Which is the odd one out? (a) wrong labels (b) photos in many lights (c) testing on training data (d) very few examples
27. 27.Which of these is bad for training a model? (a) many varied examples (b) labels added at random (c) new data for testing (d) photos in many lights
28. 28.Which of these is good for training a model? (a) blurry, unclear photos (b) new data for testing (c) testing on training data (d) labels added at random
29. 29.True or false: “examples of every type” is good for training a model. (a) True (b) False
30. 30.📚 Usually, more good examples make a model… (a) better at its task (b) slower to switch on (c) forget everything (d) change colour
31. 31.Which of these is bad for training a model? (a) blurry, unclear photos (b) clear, sharp examples (c) checking labels twice (d) photos in many lights
32. 32.🏷️ 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
33. 33.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
34. 34.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
35. 35.🏷️ 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
36. 36.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
37. 37.🏷️ 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
38. 38.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
39. 39.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
40. 40.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students