meshalalsultan/Malawi-News-Classification-Challenge

# Malawi News Classification Challenge ## Overview This project addresses the challenge of classifying news articles in Malawi using machine learning techniques. By analyzing text data, the model categorizes news articles into predefined classes, providing a tool for automated content sorting and analysis. ## Features - **Text Classification**: Automatically classify news articles into various categories. - **Machine Learning Pipeline**: Includes preprocessing, feature extraction, and model training. ## Project Structure - **News_Africa.ipynb**: Jupyter notebook containing the machine learning pipeline. - **Train.csv**: Training dataset with labeled news articles. - **Test.csv**: Test dataset for evaluating the model. - **SampleSubmission.csv**: Example of the submission format. - **spyder.py**: Python script for additional data analysis. ## Getting Started 1. **Clone the repository**: ```bash git clone github.com ``` 2. **Install required libraries**: ```bash pip install -r requirements.txt # assuming this exists ``` 3. **Explore the notebook**: ```bash jupyter notebook News_Africa.ipynb ``` ## How It Works The project uses a machine learning model trained on labeled data from `Train.csv` to predict the categories of new articles in `Test.csv`. The process involves text preprocessing, feature extraction, and applying classification algorithms. ## Contributing Contributions to improve the models or methods are welcome. Please fork the repository and submit a pull request with your changes. ## License This project is licensed under the MIT License - see the LICENSE file for details. Delve into the world of NLP and machine learning with this practical challenge on news classification!