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 metaflow

You can access tutorial by typing

metaflow

Video: Human-Centric Machine Learning Infrastructure @Netflix