MLflow vs ScalaNLP: 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, ScalaNLP is detailed as "A suite of machine learning and numerical computing libraries". ScalaNLP is a suite of machine learning and numerical computing libraries.
MLflow and ScalaNLP can be primarily classified 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, ScalaNLP provides the following key features:
- ScalaNLP is the umbrella project for several libraries:
- Breeze is a set of libraries for machine learning and numerical computing
- Epic is a high-performance statistical parser and structured prediction library
MLflow and ScalaNLP are both open source tools. ScalaNLP with 2.91K GitHub stars and 674 forks on GitHub appears to be more popular than MLflow with 23 GitHub stars and 13 GitHub forks.