Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 552 · 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.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
2. 2.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) only one kind of example (d) new data for testing
3. 3.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) clean screens (d) learn from data
4. 4.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
5. 5.True or false: “new data for testing” is bad for training a model. (a) True (b) False
6. 6.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
7. 7.Which of these is good for training a model? (a) checking labels twice (b) very few examples (c) copies of one photo (d) only one kind of example
8. 8.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) change colour (d) better at its task
9. 9.🔍 Which is the odd one out? (a) wrong labels (b) examples of every type (c) testing on training data (d) blurry, unclear photos
10. 10.Which of these is good for training a model? (a) wrong labels (b) testing on training data (c) correct labels (d) very few examples
11. 11.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
12. 12.Which of these is bad for training a model? (a) correct labels (b) checking labels twice (c) many varied examples (d) blurry, unclear photos
13. 13.Which of these is bad for training a model? (a) checking labels twice (b) wrong labels (c) correct labels (d) photos in many lights
14. 14.🏷️ 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
15. 15.True or false: “photos in many lights” is good for training a model. (a) False (b) True
16. 16.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) correct labels (d) testing on training data
17. 17.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
18. 18.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the price (c) the font size (d) a sticker on a laptop
19. 19.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
20. 20.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
21. 21.🏷️ 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
22. 22.True or false: “correct labels” is bad for training a model. (a) False (b) True
23. 23.Which of these is bad for training a model? (a) examples of every type (b) many varied examples (c) only one kind of example (d) checking labels twice
24. 24.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
25. 25.True or false: “many varied examples” is bad for training a model. (a) True (b) False
26. 26.🏷️ 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
27. 27.🔍 Which is the odd one out? (a) very few examples (b) only one kind of example (c) clear, sharp examples (d) copies of one photo
28. 28.Which of these is good for training a model? (a) testing on training data (b) many varied examples (c) wrong labels (d) labels added at random
29. 29.Which of these is bad for training a model? (a) clear, sharp examples (b) many varied examples (c) correct labels (d) copies of one photo
30. 30.🔍 Which is the odd one out? (a) correct labels (b) very few examples (c) examples of every type (d) checking labels twice
31. 31.🥭 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
32. 32.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
33. 33.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
34. 34.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
35. 35.Which of these is good for training a model? (a) copies of one photo (b) photos in many lights (c) very few examples (d) wrong labels
36. 36.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
37. 37.True or false: “labels added at random” is good for training a model. (a) True (b) False
38. 38.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
39. 39.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
40. 40.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training

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