Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 254 · 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: “testing on training data” is bad for training a model. (a) False (b) True
2. 2.🏷️ 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
3. 3.Which of these is bad for training a model? (a) correct labels (b) checking labels twice (c) blurry, unclear photos (d) clear, sharp examples
4. 4.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
5. 5.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
6. 6.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
7. 7.True or false: “examples of every type” is good for training a model. (a) False (b) True
8. 8.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) slower to switch on (d) forget everything
9. 9.🏷️ 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
10. 10.🧠 Machine learning is a way for computers to… (a) clean screens (b) print pages (c) learn from data (d) charge faster
11. 11.🏷️ 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
12. 12.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
13. 13.Which of these is good for training a model? (a) only one kind of example (b) wrong labels (c) blurry, unclear photos (d) correct labels
14. 14.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
15. 15.🔍 Which is the odd one out? (a) examples of every type (b) correct labels (c) new data for testing (d) very few examples
16. 16.🔍 Which is the odd one out? (a) examples of every type (b) only one kind of example (c) correct labels (d) new data for testing
17. 17.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
18. 18.True or false: “new data for testing” is bad for training a model. (a) True (b) False
19. 19.True or false: “correct labels” is good for training a model. (a) False (b) True
20. 20.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
21. 21.🔍 Which is the odd one out? (a) new data for testing (b) checking labels twice (c) many varied examples (d) blurry, unclear photos
22. 22.True or false: “examples of every type” is bad for training a model. (a) False (b) True
23. 23.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
24. 24.True or false: “photos in many lights” is good for training a model. (a) True (b) False
25. 25.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
26. 26.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
27. 27.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
28. 28.🐶 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
29. 29.True or false: “wrong labels” is good for training a model. (a) True (b) False
30. 30.Which of these is bad for training a model? (a) testing on training data (b) correct labels (c) checking labels twice (d) new data for testing
31. 31.Which of these is bad for training a model? (a) only one kind of example (b) clear, sharp examples (c) many varied examples (d) photos in many lights
32. 32.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it will turn yellow (d) it may get it wrong
33. 33.Which of these is good for training a model? (a) copies of one photo (b) many varied examples (c) labels added at random (d) very few examples
34. 34.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True
35. 35.🔍 Which is the odd one out? (a) testing on training data (b) wrong labels (c) labels added at random (d) photos in many lights
36. 36.🔍 Which is the odd one out? (a) testing on training data (b) clear, sharp examples (c) wrong labels (d) very few examples
37. 37.True or false: “many varied examples” is bad for training a model. (a) True (b) False
38. 38.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
39. 39.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
40. 40.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training

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