Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 504 · 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 of these is good for training a model? (a) only one kind of example (b) wrong labels (c) clear, sharp examples (d) testing on training data
2. 2.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) slower to switch on (d) forget everything
3. 3.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
4. 4.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
5. 5.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
6. 6.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
7. 7.🔍 Which is the odd one out? (a) only one kind of example (b) many varied examples (c) photos in many lights (d) correct labels
8. 8.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) copies of one photo (d) examples of every type
9. 9.True or false: “testing on training data” is good for training a model. (a) False (b) True
10. 10.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) photos in many lights (d) blurry, unclear photos
11. 11.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
12. 12.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
13. 13.Which of these is bad for training a model? (a) examples of every type (b) photos in many lights (c) only one kind of example (d) many varied examples
14. 14.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) many labelled photos (d) a song about dogs
15. 15.Which of these is good for training a model? (a) only one kind of example (b) new data for testing (c) very few examples (d) wrong labels
16. 16.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the right answer tag (d) the price
17. 17.True or false: “only one kind of example” is good for training a model. (a) False (b) True
18. 18.Which of these is good for training a model? (a) copies of one photo (b) testing on training data (c) very few examples (d) examples of every type
19. 19.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
20. 20.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
21. 21.Which of these is bad for training a model? (a) correct labels (b) blurry, unclear photos (c) many varied examples (d) examples of every type
22. 22.True or false: “new data for testing” is good for training a model. (a) False (b) True
23. 23.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
24. 24.🧠 Machine learning is a way for computers to… (a) learn from data (b) charge faster (c) clean screens (d) print pages
25. 25.🔍 Which is the odd one out? (a) blurry, unclear photos (b) examples of every type (c) only one kind of example (d) wrong labels
26. 26.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) testing on training data (b) checking labels twice (c) blurry, unclear photos (d) labels added at random
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
29. 29.🔍 Which is the odd one out? (a) many varied examples (b) clear, sharp examples (c) testing on training data (d) new data for testing
30. 30.Which of these is good for training a model? (a) wrong labels (b) many varied examples (c) very few examples (d) only one kind of example
31. 31.True or false: “copies of one photo” is bad 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.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) many varied examples (d) very few examples
34. 34.Which of these is good for training a model? (a) very few examples (b) wrong labels (c) checking labels twice (d) testing on training data
35. 35.True or false: “examples of every type” is bad for training a model. (a) True (b) False
36. 36.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
37. 37.🔍 Which is the odd one out? (a) testing on training data (b) labels added at random (c) wrong labels (d) photos in many lights
38. 38.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
39. 39.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
40. 40.True or false: “correct labels” is good for training a model. (a) True (b) False

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