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About

Manage and optimize models across the entire ML lifecycle, from experiment tracking to monitoring models in production. Achieve your goals faster with the platform built to meet the intense demands of enterprise teams deploying ML at scale. Supports your deployment strategy whether it’s private cloud, on-premise servers, or hybrid. Add two lines of code to your notebook or script and start tracking your experiments. Works wherever you run your code, with any machine learning library, and for any machine learning task. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. Monitor your models during every step from training to production. Get alerts when something is amiss, and debug your models to address the issue. Increase productivity, collaboration, and visibility across all teams and stakeholders.

About

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.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Meta machine learning platform designed to help AI practitioners and teams build reliable machine learning models for real-world application

Audience

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

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$179 per user per month
Free Version Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

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

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

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

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Comet
Founded: 2017
United States
www.comet.com

Company Information

MLflow
Founded: 2018
United States
mlflow.org

Alternatives

Alternatives

Union Cloud

Union Cloud

Union.ai
Keepsake

Keepsake

Replicate
DVC

DVC

iterative.ai

Categories

Data Science Supported
Deep Learning Supported
LLM Evaluation Supported
Machine Learning Supported

Categories

Machine Learning Features

Deep Learning Supported
ML Algorithm Library Supported
Model Training Supported
Natural Language Processing (NLP) Supported
Predictive Modeling Not Supported
Statistical / Mathematical Tools Not Supported
Templates Not Supported
Visualization Supported

Deep Learning Features

Convolutional Neural Networks Not Supported
Document Classification Not Supported
Image Segmentation Not Supported
ML Algorithm Library Supported
Model Training Supported
Neural Network Modeling Not Supported
Self-Learning Not Supported
Visualization Supported

Integrations

Amazon SageMaker Supported
Apache Spark Supported
Axolotl Supported
Google Cloud Platform Supported
Keras Supported
Ludwig Supported
TensorFlow Supported
ZenML Supported
Apolo Not Supported
Azure Data Science Virtual Machines Not Supported
Databricks Not Supported
Docker Not Supported
IBM watsonx.data integration Not Supported
OpenMetadata Not Supported
Plotly Dash Supported
Ragas Not Supported
Vectice Not Supported
Weaviate Supported
lakeFS Not Supported
navio Not Supported

Integrations

Amazon SageMaker Supported
Apache Spark Supported
Axolotl Supported
Google Cloud Platform Supported
Keras Supported
Ludwig Supported
TensorFlow Supported
ZenML Supported
Apolo Supported
Azure Data Science Virtual Machines Supported
Databricks Supported
Docker Supported
IBM watsonx.data integration Supported
OpenMetadata Supported
Plotly Dash Not Supported
Ragas Supported
Vectice Supported
Weaviate Not Supported
lakeFS Supported
navio Supported
Claim Comet and update features and information
Claim Comet and update features and information
Claim MLflow and update features and information
Claim MLflow and update features and information