MLflow

MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components: MLflow Tracking, MLflow Projects, MLflow Models, and MLflow Registry.

Logo

../_images/mlflow_mlflow-small.png

Website

https://mlflow.org/

Repository

https://github.com/mlflow/mlflow/

Byline

An open source platform for the machine learning lifecycle

License

Apache 2.0

Project age

3 years

Backers

DataBricks (Commercial Product By)

Size score (1 to 10, higher is better)

7.0

Trend score (1 to 10, higher is better)

4.25

Education Resources

URL

Resource Type

Description

https://mlflow.org/docs/latest/index.html

Documentation

Official project documentation.

Git Commit Statistics

Statistics computed using Git data through May 31, 2021.

Statistic

Lifetime

Last 12 Months

Commits

23,067

8,622

Lines committed

7,439,619

2,720,673

Unique committers

307

114

Core committers

14

13

../_images/mlflow_mlflow-monthly-commits.png

Similar Projects

Project

Size Score

Trend Score

Byline

Data Workspaces

1.75

3.25

Easy management of source data, intermediate data, and results for data science projects.

Flambe

1.25

1.25

Flambé is a machine learning experimentation framework built to accelerate the entire research life cycle. Flambé’s main objective is to provide a unified interface for prototyping models, running experiments containing complex pipelines, monitoring those experiments in real-time, reporting results, and deploying a final model for inference.

PyCaret

7.25

6.75

An open-source, low-code machine learning library in Python.