Chandru-21/MLOps_Project
An end-to-end MLOps pipeline(CI/CD/CT/CM) project for training, versioning, deploying, and monitoring machine learning models using FastAPI, Kubernetes, MLflow, DVC, Prometheus, and Grafana.
This project helps MLOps engineers set up an automated system for managing machine learning models. It takes your machine learning code and data, automatically builds, tests, and deploys your models to the cloud, making them ready for real-time predictions. The system continuously monitors model performance and retrains models with new data to ensure accuracy. This is designed for MLOps engineers or data scientists responsible for deploying and maintaining production ML systems.
No commits in the last 6 months.
Use this if you need an automated, scalable pipeline to continuously integrate, deploy, and monitor your machine learning models in a cloud environment.
Not ideal if you are looking for a simple, local model deployment solution or do not have experience with cloud infrastructure like AWS and Kubernetes.
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28
Forks
15
Language
Python
License
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Category
Last pushed
Jul 05, 2024
Commits (30d)
0
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