Build a Text Classification System | Dataford Interview Questions

Your question is Build a Text Classification System. Take a moment with it on the right.

Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).

Problem

Scenario

You are building an NLP pipeline that needs to assign text into predefined categories, such as routing support tickets, tagging documents, or labeling incoming messages. You need a practical approach that covers data preparation, feature extraction, model training, and evaluation. The goal is to produce a system that works well on real text, not just a toy dataset.

Question

What are the key steps in building a text classification system?

What this tests

Text preprocessing and tokenization
Feature extraction with TF-IDF or transformer embeddings
Supervised text classification workflow
Evaluation with class-aware metrics such as F1

Your question is Build a Text Classification System. Take a moment with it on the right.

Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).

Scenario

Question

What are the key steps in building a text classification system?

What this tests

Text preprocessing and tokenization
Feature extraction with TF-IDF or transformer embeddings
Supervised text classification workflow
Evaluation with class-aware metrics such as F1