Cortex.dev vs MLflow

MLflow vs Cortex.dev: What are the differences?

Developers describe MLflow as "An open source machine learning platform". MLflow is an open source platform for managing the end-to-end machine learning lifecycle. On the other hand, Cortex.dev is detailed as "Deploy machine learning models in production". It is an open source platform that takes machine learning models—trained with nearly any framework—and turns them into production web APIs in one command.

MLflow and Cortex.dev belong to "Machine Learning Tools" category of the tech stack.

Some of the features offered by MLflow are:

• Track experiments to record and compare parameters and results
• Package ML code in a reusable, reproducible form in order to share with other data scientists or transfer to production
• Manage and deploy models from a variety of ML libraries to a variety of model serving and inference platforms

On the other hand, Cortex.dev provides the following key features:

• Autoscaling
• Supports TensorFlow, Keras, PyTorch, Scikit-learn, XGBoost, and more
• CPU / GPU support

MLflow and Cortex.dev are both open source tools. It seems that Cortex.dev with 1.42K GitHub stars and 69 forks on GitHub has more adoption than MLflow with 43 GitHub stars and 22 GitHub forks.