Artificial Intelligence — CBSE Class 10 board question

Step 1 – Collect Training Data (Documents):

• Doc 1: "CV is an upcoming field."
• Doc 2: "Image Feature is an important part of CV."

Step 2 – Design the Vocabulary (unique words):
{ CV, is, an, upcoming, field, Image, Feature, important, part, of }
(Stop words retained; total = 10 unique words)

Step 3 – Create Document Vectors (word frequency count):

| Word | CV | is | an | upcoming | field | Image | Feature | important | part | of |
|---|---|---|---|---|---|---|---|---|---|---|
| Doc 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
| Doc 2 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 |

Step 4 – Use Vectors for ML Model:
Doc 1 → [1,1,1,1,1,0,0,0,0,0]
Doc 2 → [1,1,1,0,0,1,1,1,1,1]

These numerical vectors are fed into a Machine Learning model for text classification or analysis.

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• Examiners look for: All four steps clearly labelled with correct output at each step.
• The vocabulary must list only unique words across both documents.
• Frequency counts must be accurate — CV appears once in each document.
• The final vector representation ties the answer together; don't skip it.
• Roughly 1 mark per step — label them clearly to ensure full credit.