Added proposal demo (#2452)

proposal demo for week 4, mlflow

contributions/demo/week4/bthiberg-omidfm/README.md

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+# Assignment Proposal
+
+## Title
+
+Dynamic model rollbacks using MLflow
+
+## Names and KTH ID
+
+  - Björn Thiberg (bthiberg@kth.se)
+  - Omid Fattahi Mehr (omidfm@kth.se)
+
+## Deadline
+
+- Week 4
+
+## Category
+
+- Demo
+
+## Description
+
+We will demonstrate how to implement and automate dynamic model rollbacks using MLflow’s Model Registry. 
+
+We will look at a model in production, and simulate a model performance drop or condition (set by us) when deploying a new version of the model.
+
+Based on this condition, we will then trigger a rollback to an earlier reliable model (using Python code and the MLFlow API).
+
+The process will be verified and visualized using the MLflow GUI.
+
+**Relevance**
+
+Using version management, automatic deployment and automatic reactions based on feedback from the production environment are core parts of the devops philosophy for software development. 
+
+By doing this in an MLOps context, we demonstrate how DevOps principles can be extended for use in MLOps.
+
+There is no way to natively do this yet in MLflow, and there is even currently [an issue](https://github.com/mlflow/mlflow/issues/6180) on the main MLflow repository, showing that this is both difficult and relevant.