Netflix open-sources its human-friendly Python Framework ‘Metaflow’ to build and manage real-life data science projects with ease. Metaflow was originally developed at Netflix for addressing the needs of its data scientists who work on demanding real-life data science projects.
Metaflow provides a unified API to the infrastructure stack for the execution of data science projects (prototype to production).
Key Features:
- Use Metaflow with Data Science Python tools like PyTorch, Tensorflow, SciKit Learn, etc.
- Metaflow helps to design workflow easily with higher scalability and deployment.
- It sets the versions and tracks data and experiments automatically.
- It lets you inspect results easily in notebooks.
- In terms of scalability, Metaflow provides built-in integrations to the storage, compute, and machine learning services in the Amazon Web Services (AWS).
Github: https://github.com/Netflix/metaflow
Documentation: https://docs.metaflow.org/
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By design, Metaflow is a deceptively simple Python library as shown below:
Installation
Install metaflow from pypi:
pip install metaflowYou can access tutorial by typing
metaflowVideo: Human-Centric Machine Learning Infrastructure @Netflix
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