qooba / mlflow-feast
End to end mlflow with feast example
☆15Updated 3 years ago
Related projects: ⓘ
- A series of workshop modules introducing Feast feature store.☆19Updated 2 years ago
- PyConDE & PyData Berlin 2019 Airflow Workshop: Airflow for machine learning pipelines.☆47Updated last year
- O'Reilly Katacoda☆55Updated last year
- demo CI/CD pipeline using MLRun, Kubeflow and GitHub Actions☆48Updated 2 years ago
- ☆16Updated 3 years ago
- ☆16Updated last year
- 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…☆37Updated 3 years ago
- Example MLOps using BentoML & mlFlow☆37Updated 3 years ago
- End to End example integrating MLFlow and Seldon Core☆51Updated 3 years ago
- Repo that relates to the Medium blog 'Keeping your ML model in shape with Kafka, Airflow' and MLFlow'☆120Updated last year
- Feast AWS guide using Redshift / Spectrum / DynamoDB to build a credit scoring model☆60Updated 2 years ago
- ☆34Updated last month
- Controlling AI models distribution and versioning with MLflow and Minio/S3.☆25Updated 5 years ago
- Deployment of ML models with Serverless APIs (AWS Lambda) and Docker☆23Updated 3 years ago
- Data Science Quick Tips Repository!☆48Updated 7 months ago
- ☆15Updated this week
- Instant search for and access to many datasets in Pyspark.☆34Updated last year
- Best practices for engineering ML pipelines.☆37Updated 2 years ago
- A workshop with several modules to help learn Feast, an open-source feature store☆82Updated last week
- This is a collection of MLflow examples that you can directly run with mlflow command☆30Updated 4 years ago
- A project template for developing BYOD docker images for use in Amazon SageMaker.☆19Updated 4 years ago
- Orchestrate Spark Jobs from Kubeflow Pipelines and poll for the status.☆50Updated 2 years ago
- Guide on creating an API for serving your ML model☆65Updated 2 years ago
- End to end MLRun demos☆92Updated 2 months ago
- pycaret-demo-mlflow☆29Updated 3 years ago
- Example custom model image trainable and distributable via AWS SageMaker☆36Updated last year
- Explore tips and tricks to deploy machine learning models with Docker.☆13Updated last year
- A PaaS End-to-End ML Setup with Metaflow, Serverless and SageMaker.☆36Updated 3 years ago
- Capturing model drift and handling its response - Example webinar☆106Updated 5 years ago
- Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deploym…☆59Updated last year