Predictive Analytics For Retail

Project Description

This project represents a strategic initiative for Rossmann Pharmaceuticals, with the potential to significantly enhance the company's overall performance and competitiveness in the market.

Getting Started

Prerequisites

Python 3.x
Virtual environment (e.g., virtualenv, conda)
Required Python packages (listed in requirements.txt)

Installation

Clone the repository:

git clone https://github.com/Daniel-Andarge/AiML-predictive-analytics-for-retail.git

Change to the project directory:
```
cd your-project
```

Create a virtual environment and activate it:

# Using virtualenv
virtualenv venv
source venv/bin/activate

# Using conda
conda create -n your-env python=3.x
conda activate your-env

Install the required dependencies:
```
pip install -r requirements.txt
```

Usage

Start the Jupyter Notebook:
```
jupyter notebook
```
Navigate to the notebooks/ directory and open the relevant notebooks:
- data_understanding.ipynb
- data_cleaning.ipynb
- feature_engineering.ipynb
- eda.ipynb
- model_building.ipynb Each notebook corresponds to a step in the data analysis process, as outlined in the introduction.

Scripts and Notebooks

The project is organized into the following scripts and Jupyter Notebooks:

Data Understanding:
- data_understanding.ipynb
Data Cleaning and Preprocessing:
- data_cleaning.ipynb
Feature Engineering:
- feature_engineering.ipynb
Exploratory Data Analysis (EDA):
- eda.ipynb

4.1. EDA log File

You can Find the EDA Log file in notebooks/eda_analysis.log

Model Building:
- model_building.ipynb

Each notebook corresponds to a step in the data analysis process, as outlined in the introduction.

Dependencies

The required Python packages for this project are listed in the requirements.txt file. You can install them using the following command:

pip install -r requirements.txt

Contributing

If you would like to contribute to this project, please follow the standard GitHub workflow:

Fork the repository
Create a new branch for your feature or bug fix
Make your changes and commit them
Push your branch to your forked repository
Create a pull request to the main repository

License

This project is licensed under the MIT License.

Acknowledgments

Thank you to the contributors and the open-source community for their support and resources.