Welcome! This is a repository for a MLOps project with Kedro and MLflow!
Goal of this project is to create a complete MLOps pipeline to predict house pricing.
The House Pricing dataset from Kaggle is utilized for the purpose of creating and evaluating pipelines. Various pipelines were developed for different tasks, which can be found in the pipeline_registry.py file.
The project covers following aspects of MLOps:
- Experimentation and model versioning
- Data and concept drift evaluation
- Data quality tests
- Unit function tests
In this repository following key frameworks and libraries were used:
python3 -m venv .mlops-env
source .mlops-env/bin/activate
pip install --upgrade pip
pip install -r requirements.txt