m-nanda/End-to-End-ML

An "End-to-End Machine Learning" project focuses on building a machine learning pipeline that prevents data leakage and deploys the model with microservice-architecture for real-world use.

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Emerging

This project helps data science teams build and deploy reliable machine learning models. It takes your raw dataset and produces a trained model, along with a comprehensive report on its performance. The model is then deployed as an API, ready to integrate into web applications, ensuring secure and consistent real-world predictions. It's for data scientists or MLOps engineers who need to move models from development to production efficiently.

No commits in the last 6 months.

Use this if you need to quickly deploy machine learning models as secure, authenticated APIs for real-world applications, while ensuring data integrity and automated performance reporting.

Not ideal if you are looking for advanced model development techniques or a deep dive into specific machine learning algorithms, as this project prioritizes the end-to-end pipeline and deployment.

Machine Learning Operations Model Deployment Data Leakage Prevention API Development Predictive Analytics
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 15 / 25

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Stars

15

Forks

4

Language

Python

License

MIT

Last pushed

Aug 05, 2025

Commits (30d)

0

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