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About

The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run Kubeflow. Kubeflow provides a custom TensorFlow training job operator that you can use to train your ML model. In particular, Kubeflow's job operator can handle distributed TensorFlow training jobs. Configure the training controller to use CPUs or GPUs and to suit various cluster sizes. Kubeflow includes services to create and manage interactive Jupyter notebooks. You can customize your notebook deployment and your compute resources to suit your data science needs. Experiment with your workflows locally, then deploy them to a cloud when you're ready.

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
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Anyone looking for a Machine Learning toolkit for Kubernetes

Audience

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

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

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

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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
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Kubeflow
www.kubeflow.org

Company Information

MLflow
Founded: 2018
United States
mlflow.org

Alternatives

Vertex AI

Vertex AI

Google

Alternatives

Union Cloud

Union Cloud

Union.ai
Union Cloud

Union Cloud

Union.ai
Vertex AI

Vertex AI

Google

Categories

Categories

Integrations

Azure Marketplace
Comet LLM
Flyte
Kedro
Kubernetes
Robust Intelligence
Superwise
Union Cloud
ZenML
Apache Spark
Apolo
Axolotl
Civo
Giskard
H2O.ai
HoneyHive
Microsoft 365
PredictKube
Unity Catalog
navio

Integrations

Azure Marketplace
Comet LLM
Flyte
Kedro
Kubernetes
Robust Intelligence
Superwise
Union Cloud
ZenML
Apache Spark
Apolo
Axolotl
Civo
Giskard
H2O.ai
HoneyHive
Microsoft 365
PredictKube
Unity Catalog
navio
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Claim Kubeflow and update features and information
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