deliveryhero / pyconde2019-airflow-ml-workshopLinks
PyConDE & PyData Berlin 2019 Airflow Workshop: Airflow for machine learning pipelines.
☆47Updated last year
Alternatives and similar repositories for pyconde2019-airflow-ml-workshop
Users that are interested in pyconde2019-airflow-ml-workshop are comparing it to the libraries listed below
Sorting:
- Repo that relates to the Medium blog 'Keeping your ML model in shape with Kafka, Airflow' and MLFlow'☆120Updated 2 years ago
- Best practices for engineering ML pipelines.☆35Updated 3 years ago
- ☆18Updated 3 years ago
- ☆19Updated 4 years ago
- Pytest for Data Science Beginners☆58Updated 6 years ago
- Blog post on ETL pipelines with Airflow☆23Updated 5 years ago
- The practical use-cases of how to make your Machine Learning Pipelines robust and reliable using Apache Airflow.☆52Updated 2 years ago
- Managing machine learning life-cycle with MLflow tutorial☆23Updated 2 years ago
- Airflow training for the crunch conf☆105Updated 6 years ago
- Companion Notebooks and Data for Data Science with Python and Dask from Manning Publications☆52Updated 4 years ago
- ☆28Updated 3 years ago
- 🐍💨 Airflow tutorial for PyCon 2019☆86Updated 2 years ago
- Data lake, data warehouse on GCP☆56Updated 3 years ago
- Deploy A/B testing infrastructure in a containerized microservice architecture for Machine Learning applications.☆40Updated 5 months ago
- How to do data science with Optimus, Spark and Python.☆19Updated 5 years ago
- ☆16Updated 7 years ago
- (project & tutorial) dag pipeline tests + ci/cd setup☆88Updated 4 years ago
- Partly lecture and partly a hands-on tutorial and workshop, this is a three part series on how to get started with MLflow. In this four p…☆35Updated 5 years ago
- Capturing model drift and handling its response - Example webinar☆108Updated 5 years ago
- ☆49Updated 3 years ago
- Partly lecture and partly a hands-on tutorial and workshop, this is a three part series on how to get started with MLflow. In this four p…☆39Updated 4 years ago
- ☆86Updated 2 years ago
- ☆16Updated 2 years ago
- Example using Great Expectations to Validate Data in a scikit-learn Pipeline☆21Updated 4 years ago
- scaffold of Apache Airflow executing Docker containers☆85Updated 2 years ago
- Guide for applying Unit Testing in data-driven projects☆19Updated 5 years ago
- Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deploym…☆62Updated 2 years ago
- Demo on how to use Prefect with Docker☆25Updated 2 years ago
- Scaling Python Machine Learning☆46Updated last year
- O'Reilly Katacoda☆56Updated 2 years ago