Prevision

Prevision

Prevision.io
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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.

About

Building a model is an iterative process that can take weeks, months, or even years, and reproducing model results, maintaining version control, and auditing past work are complex. Model building is an iterative process. Ideally, you record not only each step but also how you arrived there. A model shouldn’t be a file hidden away somewhere, but instead a tangible object that all parties can track and analyze consistently. Prevision.io allows you to record each experiment as you train it along with its characteristics, automated analyses, and versions as your project progress, whether you created it using our AutoML or your own tools. Automatically experiment with dozens of feature engineering strategies and algorithm types to build highly performant models. In a single command, the engine automatically tries out different feature engineering strategies for every type of data (e.g. tabular, text, images) to maximize the information in your datasets.

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

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

Audience

Developer teams and companies seeking a solution to track, record, and compare the iterations of ML experiments

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

MLflow
Founded: 2018
United States
mlflow.org

Company Information

Prevision.io
France
prevision.io

Alternatives

Union Cloud

Union Cloud

Union.ai

Alternatives

DVC

DVC

iterative.ai

Categories

Categories

Machine Learning Features

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

Integrations

Apache Spark
Apolo
Azure Machine Learning
Comet LLM
Cranium
CrateDB
Dagster
Databricks
Determined AI
Flyte
H2O.ai
IBM watsonx.data integration
Microsoft 365
OpenMetadata
Ragas
Superwise
TensorFlow
TrueFoundry
UbiOps
Vectice

Integrations

Apache Spark
Apolo
Azure Machine Learning
Comet LLM
Cranium
CrateDB
Dagster
Databricks
Determined AI
Flyte
H2O.ai
IBM watsonx.data integration
Microsoft 365
OpenMetadata
Ragas
Superwise
TensorFlow
TrueFoundry
UbiOps
Vectice
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Claim MLflow and update features and information
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