Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 229 · 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 is the odd one out? (a) only one kind of example (b) clear, sharp examples (c) photos in many lights (d) correct labels
2. 2.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) photos in many lights (d) only one kind of example
3. 3.Which of these is bad for training a model? (a) checking labels twice (b) examples of every type (c) photos in many lights (d) wrong labels
4. 4.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
5. 5.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
6. 6.True or false: “checking labels twice” is good for training a model. (a) False (b) True
7. 7.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
8. 8.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) a list of rules only (d) many labelled photos
9. 9.🏷️ 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
10. 10.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
11. 11.True or false: “new data for testing” is good for training a model. (a) True (b) False
12. 12.🔍 Which is the odd one out? (a) clear, sharp examples (b) labels added at random (c) many varied examples (d) examples of every type
13. 13.True or false: “new data for testing” is bad for training a model. (a) True (b) False
14. 14.Which of these is bad for training a model? (a) examples of every type (b) correct labels (c) copies of one photo (d) many varied examples
15. 15.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
16. 16.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
17. 17.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will be perfect (c) it will turn yellow (d) it will shut down
18. 18.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) copies of one photo (d) correct labels
19. 19.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) a sticker on a laptop (d) the price
20. 20.🔍 Which is the odd one out? (a) photos in many lights (b) correct labels (c) many varied examples (d) copies of one photo
21. 21.True or false: “very few examples” is good for training a model. (a) True (b) False
22. 22.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
23. 23.🔍 Which is the odd one out? (a) only one kind of example (b) checking labels twice (c) wrong labels (d) blurry, unclear photos
24. 24.True or false: “correct labels” is bad for training a model. (a) False (b) True
25. 25.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
26. 26.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
27. 27.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
28. 28.Which of these is good for training a model? (a) blurry, unclear photos (b) checking labels twice (c) testing on training data (d) only one kind of example
29. 29.True or false: “very few examples” is bad for training a model. (a) False (b) True
30. 30.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) print pages (d) clean screens
31. 31.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) only one kind of example (b) clear, sharp examples (c) copies of one photo (d) blurry, unclear photos
33. 33.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
34. 34.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
35. 35.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
36. 36.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
37. 37.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
38. 38.True or false: “photos in many lights” is good for training a model. (a) True (b) False
39. 39.True or false: “copies of one photo” is good for training a model. (a) False (b) True
40. 40.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam

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