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# Somali Text Classification (NLP Project)
This project builds a simple text classification model for the Somali language.
It demonstrates how to preprocess text, extract features with TF-IDF, and train a machine learning model for classification.
## Features
- Somali text preprocessing
- TF-IDF feature extraction
- Baseline model: Logistic Regression
- Evaluation using Accuracy, Precision, Recall, and F1-score
## Repository Structure
```
somali-text-classification/
│── data/ # (optional) store datasets here
│── notebooks/
│ └── somali_text_classification.ipynb
│── src/
│ ├── preprocess.py
│ ├── train.py
│ └── evaluate.py
│── requirements.txt
│── README.md
```
## Installation
```bash
git clone
github.com
cd somali-text-classification
pip install -r requirements.txt
```
## Usage
Run the notebook for an end-to-end demo:
```bash
jupyter notebook notebooks/somali_text_classification.ipynb
```
Or train from command line:
```bash
python src/train.py
```
## Future Work
- Expand dataset with more Somali texts
- Add deep learning models (LSTMs, Transformers)
- Deploy with FastAPI/Streamlit
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# Somali-Text-Classification-Project
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