Plant-Disease-Classification-using-MLflow-and-DVC

End to end production grade Plant Disease Classification using MLflow and DVC

⚠️Disclaimer:

This project is a proof of concept (POC) and is meant for educational purposes only. The dataset used in this project does not come with any guarantees, and its accuracy or reliability is not verified. Therefore, it should not be used for real-world farming decisions, and the creator holds no responsibility for any outcomes if it is used in such a way. However, this project demonstrates how Machine Learning and Deep Learning can potentially be applied to precision farming if developed on a larger scale with authentic and verified data.

📚Sources:

• Plant Disease Dataset

• My Notebook

🧰Tools Used:

• Python Programming Language.
• Python Flask.
• MLOps with DagsHub.
• HTML, and CSS.
• TensorFlow.
• Git, GitHub, and GitHub Actions.
• AWS.
• Docker

⚒️Project Workflow:

1. Update config.yaml
2. Update params.yaml
3. Update the entity.
4. Update the configuration manager in src config.
5. Update the components.
6. Update the pipeline.
7. Update the main.py(endpoint)
8. Update the dvc.yaml.

💻How to use: