Renal Disease Classifier with MLflow and DVC

This repository contains a project for classifying renal disease using machine learning techniques. The project leverages MLflow for tracking experiments and DVC (Data Version Control) for managing data and model versions.

Table of Contents

1. Project Overview
2. Getting Started 2a. Prerequisites 2b. Installation
3. Usage 3a. Running the Application 3b. MLflow Tracking
4. Project Structure
5. Contributing

1. Project Overview

The Renal Disease Classifier project aims to build a machine learning model to classify renal disease. The project uses a combination of Python, MLflow, and DVC to ensure reproducibility and effective data management.

2. Getting Started

2a. Prerequisites

1. Python 3.8 or higher
2. Docker
3. Git
4. DVC
5. MLflow

2b. Installation

1. Clone the repository:

git clone https://github.com/titan-exasaur/RENAL-DISEASE-CLASSIFIER-MLFLOW-DVC.git
cd RENAL-DISEASE-CLASSIFIER-MLFLOW-DVC

2. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required Python packages:

pip install -r requirements.txt

3. Usage

3a. Running the Application

1. To run the application, use the following command:

python main.py

3b. MLflow Tracking

To start the MLflow UI for tracking experiments, run:

mlflow repro

3. Then, navigate to http://localhost:5000 to access the MLflow UI.

4. Project Structure

.
├── .dvc/                  # DVC specific files
├── .github/               # GitHub workflows and configurations
├── build/                 # Build related files
├── config/                # Configuration files
├── logs/                  # Logs directory
├── model/                 # Model related files
├── research/              # Research related files
├── src/                   # Source code
│   ├── data/              # Data processing scripts
│   ├── models/            # Model definition scripts
│   ├── utils/             # Utility scripts
├── templates/             # Template files
├── .dvcignore             # DVC ignore file
├── .gitattributes         # Git attributes file
├── .gitignore             # Git ignore file
├── Dockerfile             # Dockerfile for containerization
├── app.py                 # Flask application
├── dvc.lock               # DVC lock file
├── dvc.yaml               # DVC pipeline file
├── main.py                # Main script
├── params.yaml            # Parameters file
├── requirements.txt       # Python requirements
├── scores.json            # Scores file
├── setup.py               # Setup script for packaging
├── template.py            # Template script
└── README.md              # Readme file

5. Contributing

Contributions are welcome! Please follow these steps to contribute:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -m 'Add some feature').
5. Push to the branch (git push origin feature-branch).
6. Open a pull request.