data-logistic-analysis

Overview

This project is my first venture into the domain of data analysis. It aims to explore logistic regression and its application in analyzing datasets.

Project Structure

• data/: This directory contains sample datasets for analysis.
• notebooks/: This directory holds Jupyter notebooks where the analysis is conducted.
• scripts/: Any scripts utilized for data preprocessing, model training, or analysis can be found here.
• results/: This directory stores any output files or visualizations generated during the analysis.

Requirements

• Python 3.x
• Jupyter Notebook
• Pandas
• NumPy
• Matplotlib
• Scikit-learn

Usage

1. Clone this repository to your local machine.
2. Navigate to the project directory.
3. Set up a virtual environment (optional but recommended).
4. Install the required dependencies using pip install -r requirements.txt.
5. Explore the notebooks in the notebooks/ directory to understand the analysis process.
6. Modify or create new notebooks/scripts as needed for your analysis.
7. Execute the notebooks/scripts to perform data analysis.

Contributing

Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request.

License

This project is licensed under the MIT License.