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ai agents
A text classifier that beats a simple baseline
Classify real text, starting from the dumbest thing that could work.
Why it matters
Starting from a baseline and doing error analysis is the professional habit that most self-taught machine learning skips entirely.
What you build
- A trivial baseline with a measured score
- A bag-of-words model that beats it
- Error analysis on what it gets wrong
- A held-out test result reported once
If you want more
- Fine-tune a transformer and compare
- Deploy it behind an API
Build it
- Predict the majority class and record the score
- Train a simple model and beat the baseline
Material for the whole build
Shows the disciplined loop rather than a notebook that reports one flattering number.
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