Related Products
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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.
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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.
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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
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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
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Audience
Meta machine learning platform designed to help AI practitioners and teams build reliable machine learning models for real-world application
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Audience
Companies looking for an open source platform solution for the machine learning lifecycle
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
$179 per user per month
Free Version
Supported
Free Trial
Not Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationComet
Founded: 2017
United States
www.comet.com
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Company InformationMLflow
Founded: 2018
United States
mlflow.org
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Alternatives |
Alternatives |
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Categories |
Categories |
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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
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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
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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
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