Audience

Companies looking for an open source platform solution for the machine learning lifecycle

About 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. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects.

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Integrations

API:
Yes, MLflow offers API access
See Integrations

Ratings/Reviews

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Company Information

MLflow
Founded: 2018
United States
mlflow.org

Videos and Screen Captures

MLflow Screenshot 1
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Product Details

Platforms Supported
Cloud
Training
Documentation
Support
Online

MLflow Frequently Asked Questions

Q: What kinds of users and organization types does MLflow work with?
Q: What languages does MLflow support in their product?
Q: What kind of support options does MLflow offer?
Q: What other applications or services does MLflow integrate with?
Q: Does MLflow have an API?
Q: What type of training does MLflow provide?

MLflow Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Templates
Visualization
Statistical / Mathematical Tools

MLflow Additional Categories