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readme.md

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 # End-to-End MLOps
 
+This project explores Machine Learning Operations (MLOps)
+as a solution to the challenges of deploying and maintaining ML models in production.
+It implements a flexible multi-container system that enables
+automated training, deployment, monitoring, and optimization of ML models.
+The approach is demonstrated using a distance measurement application with a rearview camera
+but is designed to be easily adaptable for various ML applications.
+The system ensures scalability, reproducibility, and maintainability,
+making it suitable for a wide range of ML use cases.
+
+This project is closely related to my Bachelor's thesis,
+which was developed in collaboration with Bosch Engineering GmbH and Hochschule Heilbronn.
+The thesis explores the concept of Machine Learning Operations (MLOps)
+and its practical implementation.
+You can find the full thesis [here](https://www.mbenediktf.de/end-to-end-mlops/).
+
+## System architecture
+
 ![Systemarchitektur](src/system_architecture.jpg)