Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 222 · 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) labels added at random (b) clear, sharp examples (c) testing on training data (d) very few examples
2. 2.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) a list of rules only (c) many labelled photos (d) one single photo
3. 3.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
4. 4.🏷️ 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
5. 5.Which of these is good for training a model? (a) correct labels (b) very few examples (c) wrong labels (d) blurry, unclear photos
6. 6.Which of these is good for training a model? (a) labels added at random (b) blurry, unclear photos (c) testing on training data (d) clear, sharp examples
7. 7.True or false: “very few examples” is bad for training a model. (a) False (b) True
8. 8.🔍 Which is the odd one out? (a) new data for testing (b) correct labels (c) testing on training data (d) clear, sharp examples
9. 9.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) better at its task (d) slower to switch on
10. 10.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
11. 11.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) new data for testing (d) very few examples
12. 12.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
13. 13.🏷️ 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
14. 14.Which of these is bad for training a model? (a) wrong labels (b) clear, sharp examples (c) photos in many lights (d) examples of every type
15. 15.Which of these is good for training a model? (a) examples of every type (b) wrong labels (c) very few examples (d) copies of one photo
16. 16.🏷️ What is a “label” in machine learning? (a) the font size (b) the price (c) a sticker on a laptop (d) the right answer tag
17. 17.True or false: “correct labels” is good for training a model. (a) False (b) True
18. 18.🔍 Which is the odd one out? (a) photos in many lights (b) many varied examples (c) only one kind of example (d) new data for testing
19. 19.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
20. 20.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
21. 21.🏷️ 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
22. 22.🔍 Which is the odd one out? (a) blurry, unclear photos (b) correct labels (c) checking labels twice (d) examples of every type
23. 23.🔍 Which is the odd one out? (a) wrong labels (b) blurry, unclear photos (c) copies of one photo (d) photos in many lights
24. 24.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
25. 25.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
26. 26.🏷️ 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
27. 27.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
28. 28.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
29. 29.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
30. 30.True or false: “wrong labels” is bad for training a model. (a) True (b) False
31. 31.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
32. 32.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) learn from data (d) print pages
33. 33.🔍 Which is the odd one out? (a) many varied examples (b) examples of every type (c) photos in many lights (d) wrong labels
34. 34.Which of these is bad for training a model? (a) photos in many lights (b) examples of every type (c) labels added at random (d) new data for testing
35. 35.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
36. 36.True or false: “testing on training data” is good for training a model. (a) True (b) False
37. 37.True or false: “testing on training data” is bad for training a model. (a) False (b) True
38. 38.🔍 Which is the odd one out? (a) blurry, unclear photos (b) very few examples (c) labels added at random (d) many varied examples
39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
40. 40.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True

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