AI/ML & Data
Sentiment Classifier
Text-to-sentiment classification — trained on a synthetic dataset, and we say so.
A text classification model mapping reviews to sentiment. Built as a methodology demo on synthetic data — a caveat we state up front.
01
The problem
Feedback arrives faster than anyone reads it; teams need an automatic first read of what's positive, negative, or drifting.
02
Our approach
A standard NLP pipeline — preprocessing, vectorization, model comparison — kept deliberately transparent so the method transfers to real client corpora.
03
The outcome
A clean, transferable sentiment pipeline; production versions retrain on the client's own labeled data.
Highlights
- Transparent NLP pipeline
- Method transfers to real corpora
