MACHINE LEARNING // NLP CLASSIFICATION // 08

MBTI Classifier NLP.

Built a Streamlit NLP application that converts user text into MBTI-style labels using text cleaning, bag-of-words features, and four binary Naive Bayes classifiers.

CLIENT

Portfolio ML Project

ROLE

NLP Developer

CHALLENGE

The project required a traceable text-classification pipeline while preventing the resulting labels from being presented as psychological assessment.

SOLUTION

Implemented URL and punctuation removal, lowercase tokenization, English stopword filtering, vocabulary extraction, four trait classifiers, combined type output, and confidence display for each trait.

KEY FEATURES

01User text input
02NLTK text preprocessing
03Bag-of-words feature extraction
04Four binary trait classifiers
05Combined MBTI-style output
06Trait probability display
07Assessment limitation notice

TECHNOLOGY

PythonStreamlitNLTKscikit-learnPandasNumPy

RESULTS

Delivered a deployed NLP demonstration that exposes the preprocessing, trait-classification, and probability-output flow through a Streamlit interface.

PROJECT LINKS

LIVE DEMOVISIT

GITHUBVIEW

NOTE

The output is a dataset-dependent machine learning prediction. It is not a psychological test, diagnosis, counseling tool, hiring assessment, or formal personality evaluation.

NEXT PROJECT

Decision Tree Classification.

MACHINE LEARNING // DECISION TREE