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.
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.
Stars
15
Forks
4
Language
Python
License
MIT
Category
Last pushed
Aug 05, 2025
Commits (30d)
0
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