Predict-MBTI-Types is an exploratory project that aims to predict MBTI (Myers-Briggs Type Indicator) personality types using score-based input features instead of text. Built purely in a Jupyter Notebook, this project demonstrates a basic ML pipeline and opens up opportunities for future development in personality modeling based on structured data.
| Category | Tools & Libraries |
|---|---|
| Language | Python |
| ML Framework | scikit-learn |
| Data Handling | pandas, numpy |
| Visualization | matplotlib, seaborn |
| Environment | Jupyter Notebook |
| Versioning | Git, GitHub |
- Score-based MBTI classification (non-textual approach)
- Simple and readable ML pipeline using logistic regression
- Jupyter Notebook format for ease of experimentation
- Well-structured dataset for reproducibility
Live demo is currently not available. Future deployment planned.
- Clone the Repository
- Create and Activate Virtual Environment
python3 -m venv venv source venv/bin/activate - Install Dependencies
pip install -r requirements.txt
- Run the Notebook Open the notebook file predict-mbti-types.ipynb in Jupyter and execute all cells.
- Add model evaluation metrics (accuracy, F1-score, confusion matrix)
- Expand dataset to include multiple input types (e.g., text, hybrid)
- Create web-based interactive demo (e.g., Streamlit or Flask)
- Support additional classification algorithms and benchmarking
This project is collaboratively developed by:
Interested in collaborating or enhancing this project? Reach me at LinkedIn or visit dodevca.com.
Initiated by Dodevca & Team, open for collaboration and continuous refinement.