MLflow vs MXNet

MLflow vs MXNet: What are the differences?

MLflow: An open source machine learning platform. MLflow is an open source platform for managing the end-to-end machine learning lifecycle; MXNet: A flexible and efficient library for deep learning. A deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, it contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly.

MLflow and MXNet can be categorized as "Machine Learning" tools.

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, MXNet provides the following key features:

• Lightweight
• Portable
• Flexible distributed/Mobile deep learning

MLflow and MXNet are both open source tools. MXNet with 17.5K GitHub stars and 6.21K forks on GitHub appears to be more popular than MLflow with 30 GitHub stars and 13 GitHub forks.