A simple Machine Learning project that classifies a person as Introvert or Extrovert based on input features. (No feelings were hurt during model training, only the GPU was.)
- Data preprocessing pipeline
- Model training & evaluation
- Supports multiple classifiers (MLP, SVC, Random Forest, etc.)
- Implemented in Jupyter Notebook (.ipynb)
├── introvert_extrovert.ipynb # Main notebook with full pipeline
├── README.md # Project documentation (you are here 👀)
└── data.csv (optional) # Dataset if used locally
Make sure you have Python 3.8+ installed.
pip install numpy pandas scikit-learn matplotlib- Open the notebook:
jupyter notebook introvert_extrovert.ipynb- Run all cells to train and test the model
- View evaluation metrics and predictions inside the notebook
You can test different algorithms, for example:
- Neural Network (MLPClassifier)
- SVM (SVC)
- RandomForestClassifier
Results are displayed in the notebook using:
- Accuracy
- MAE / MSE (optional)
- Confusion matrix
- Classification report
- If your data looks like numbers but is actually text, convert it properly before training
- Scale features when using SVM or Neural Networks
- Regression models work for numbers… but personalities need classification 😎
Pull requests are welcome! If you find bugs, open an issue. If you find the perfect personality formula, call me. We’ll both become billionaires.
Free to use for educational purposes.