Build Your Own AI Project Worksheet
AI tip (Accuracy = correct ÷ total × 100): Steps: 1 choose a problem → 2 collect examples → 3 label them → 4 check and correct bad labels (clean the data) → 5 split into training and test sets → 6 train → 7 test with new examples → 8 measure accuracy → 9 improve the data and retest. Accuracy = correct ÷ total × 100. Wrong = total − correct. Expected right = accuracy ÷ 100 × total. Keep some examples apart for testing (for example one fifth); the rest are for training.
NameDateTime takenScore ___ / 40
- 1.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 9 right and Model B got 7 right. How many percentage points more accurate is Model A?
- 2.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a new colour screen (b) fewer examples (c) a louder speaker (d) more labelled examples
- 3.🧪 Why must you test a model on examples it has NOT seen? (a) to see if it learned (b) to make it bigger (c) to make it faster (d) to save paper
- 4.⚖️ Two bird-song app models were tested on the same 25 bird songs. Model A got 24 right and Model B got 16 right. How many percentage points more accurate is Model A?
- 5.🎯 Nisha’s fruit sorter was tested on 5 new fruit photos and got 3 right. What is its accuracy in percent?
- 6.🎯 Nisha’s fruit sorter was tested on 4 new fruit photos and got 4 right. What is its accuracy in percent?
- 7.📋 Planning an AI project: which comes first — calculate percent right or try unseen examples? (a) calculate percent right (b) try unseen examples
- 8.❌ Ananya’s handwriting reader was tested on 28 new handwritten letters and got 22 right. How many did it get wrong?
- 9.📦 Kabir collected 190 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
- 10.🧪 What is accuracy? (a) correct + total (b) total − correct (c) correct ÷ total × 100 (d) total × 2
- 11.📦 Rohan collected 170 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
- 12.🎯 Aarav’s recycling sorter is 90% accurate. If it is tested on 100 new waste photos, how many should it get right?
- 13.🎯 Vihaan’s fruit sorter is 50% accurate. If it is tested on 80 new fruit photos, how many should it get right?
- 14.🎯 Arjun’s leaf identifier was tested on 25 new leaf photos and got 13 right. What is its accuracy in percent?
- 15.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 20 right and Model B got 16 right. How many percentage points more accurate is Model A?
- 16.📦 Saanvi collected 50 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
- 17.🎯 Rohan’s handwriting reader was tested on 10 new handwritten letters and got 10 right. What is its accuracy in percent?
- 18.📋 Planning an AI project: which comes first — try unseen examples or set aside test photos? (a) try unseen examples (b) set aside test photos
- 19.📦 Nisha collected 90 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
- 20.📋 Planning an AI project: which comes first — correct bad labels or improve data, retest? (a) correct bad labels (b) improve data, retest
- 21.⚖️ Two spam spotter models were tested on the same 10 messages. Model A got 9 right and Model B got 6 right. How many percentage points more accurate is Model A?
- 22.🎯 Nisha’s bird-song app is 90% accurate. If it is tested on 100 new bird songs, how many should it get right?
- 23.📦 Saanvi collected 200 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
- 24.📋 Planning an AI project: which comes first — correct bad labels or test on new photos? (a) correct bad labels (b) test on new photos
- 25.📋 Planning an AI project: which comes first — tag each photo by type or try unseen examples? (a) tag each photo by type (b) try unseen examples
- 26.🎯 Diya’s recycling sorter was tested on 4 new waste photos and got 2 right. What is its accuracy in percent?
- 27.🎯 Meera’s handwriting reader is 90% accurate. If it is tested on 20 new handwritten letters, how many should it get right?
- 28.🎯 Kabir’s fruit sorter is 50% accurate. If it is tested on 100 new fruit photos, how many should it get right?
- 29.🎯 Nisha’s fruit sorter is 80% accurate. If it is tested on 30 new fruit photos, how many should it get right?
- 30.📦 Tara collected 120 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
- 31.📦 Ishaan collected 140 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
- 32.🎯 Saanvi’s bird-song app was tested on 50 new bird songs and got 30 right. What is its accuracy in percent?
- 33.📋 Planning an AI project: which comes first — tag each photo by type or choose what to sort? (a) tag each photo by type (b) choose what to sort
- 34.🎯 Vihaan’s leaf identifier was tested on 4 new leaf photos and got 4 right. What is its accuracy in percent?
- 35.📋 Planning an AI project: which comes first — test on new photos or work out the accuracy? (a) test on new photos (b) work out the accuracy
- 36.⚖️ Two handwriting reader models were tested on the same 10 handwritten letters. Model A got 9 right and Model B got 8 right. How many percentage points more accurate is Model A?
- 37.📋 Planning an AI project: which comes first — recheck every label or let it learn patterns? (a) recheck every label (b) let it learn patterns
- 38.📦 Ishaan collected 170 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
- 39.🎯 Vihaan’s spam spotter is 50% accurate. If it is tested on 40 new messages, how many should it get right?
- 40.📋 Planning an AI project: which comes first — try unseen examples or split train and test? (a) try unseen examples (b) split train and test
Answer key
- 20
- more labelled examples
- to see if it learned
- 32
- 60
- 100
- try unseen examples
- 6
- 152
- correct ÷ total × 100
- 136
- 90
- 40
- 52
- 16
- 40
- 100
- set aside test photos
- 72
- correct bad labels
- 30
- 90
- 160
- correct bad labels
- tag each photo by type
- 50
- 18
- 50
- 24
- 96
- 112
- 60
- choose what to sort
- 100
- test on new photos
- 10
- recheck every label
- 136
- 20
- split train and test
Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students