Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 558 · 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: testing on training data? (a) bad for training (b) good for training
2. 2.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
3. 3.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
4. 4.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
5. 5.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) change colour (d) better at its task
6. 6.True or false: “labels added at random” is bad for training a model. (a) True (b) False
7. 7.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
8. 8.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
9. 9.Which of these is bad for training a model? (a) correct labels (b) very few examples (c) examples of every type (d) many varied examples
10. 10.True or false: “wrong labels” is good for training a model. (a) True (b) False
11. 11.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
12. 12.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
13. 13.🏷️ 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
14. 14.Which of these is good for training a model? (a) new data for testing (b) only one kind of example (c) wrong labels (d) testing on training data
15. 15.🏷️ 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
16. 16.🧠 Machine learning is a way for computers to… (a) clean screens (b) print pages (c) charge faster (d) learn from data
17. 17.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
18. 18.True or false: “checking labels twice” is good for training a model. (a) True (b) False
19. 19.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
21. 21.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
22. 22.True or false: “photos in many lights” is good for training a model. (a) True (b) False
23. 23.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
24. 24.Which of these is bad for training a model? (a) examples of every type (b) correct labels (c) clear, sharp examples (d) labels added at random
25. 25.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
26. 26.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
27. 27.🔍 Which is the odd one out? (a) wrong labels (b) correct labels (c) blurry, unclear photos (d) testing on training data
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
29. 29.Which of these is bad for training a model? (a) checking labels twice (b) photos in many lights (c) only one kind of example (d) clear, sharp examples
30. 30.True or false: “correct labels” is good for training a model. (a) True (b) False
31. 31.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) copies of one photo (d) correct labels
32. 32.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the font size (d) the right answer tag
33. 33.True or false: “new data for testing” is good for training a model. (a) False (b) True
34. 34.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
35. 35.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
36. 36.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will turn yellow (c) it may get it wrong (d) it will be perfect
37. 37.True or false: “very few examples” is good for training a model. (a) True (b) False
38. 38.True or false: “many varied examples” is good for training a model. (a) True (b) False
39. 39.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
40. 40.Which of these is good for training a model? (a) only one kind of example (b) copies of one photo (c) blurry, unclear photos (d) clear, sharp examples

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