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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Utilize Subversion to manage versions of individual projects or entire repositories outside of ODI, incorporating automated dependency management for ODI. The automated build process generates a release for either a single project or a full repository, resulting in an archive that can be stored for future reference. The automated deployment initiates from this archive, allowing for the restoration of the project to any designated test or production repository. Repositories are created automatically, providing a streamlined environment. As developers version their code and support for parallel development is enabled, the overall code base becomes more robust. This efficient management of various releases and hot fixes enhances speed, transparency, and reliability. Once a developer commits their code to the version control system, a comprehensive and automated workflow encompassing build, deployment, approval, and notification is activated. This entire process is designed to be dependable, reproducible, and traceable, enabling more frequent deployments and smoother transitions. By adopting this automated system, organizations can significantly improve their development cycles and overall project management efficiency.

Description

MLflow is an open-source suite designed to oversee the machine learning lifecycle, encompassing aspects such as experimentation, reproducibility, deployment, and a centralized model registry. The platform features four main components that facilitate various tasks: tracking and querying experiments encompassing code, data, configurations, and outcomes; packaging data science code to ensure reproducibility across multiple platforms; deploying machine learning models across various serving environments; and storing, annotating, discovering, and managing models in a unified repository. Among these, the MLflow Tracking component provides both an API and a user interface for logging essential aspects like parameters, code versions, metrics, and output files generated during the execution of machine learning tasks, enabling later visualization of results. It allows for logging and querying experiments through several interfaces, including Python, REST, R API, and Java API. Furthermore, an MLflow Project is a structured format for organizing data science code, ensuring it can be reused and reproduced easily, with a focus on established conventions. Additionally, the Projects component comes equipped with an API and command-line tools specifically designed for executing these projects effectively. Overall, MLflow streamlines the management of machine learning workflows, making it easier for teams to collaborate and iterate on their models.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker No 
Apache Spark No 
Apolo No 
Aporia No 
Axolotl No 
Azure Marketplace No 
CrateDB No 
Docker No 
Google Cloud Platform No 
HoneyHive No 
LLaMA-Factory No 
LiteLLM No 
Ludwig No 
OpenMetadata No 
TrueFoundry No 
Vectice No 
ZenML No 
lakeFS No 

Integrations

Amazon SageMaker Yes 
Apache Spark Yes 
Apolo Yes 
Aporia Yes 
Axolotl Yes 
Azure Marketplace Yes 
CrateDB Yes 
Docker Yes 
Google Cloud Platform Yes 
HoneyHive Yes 
LLaMA-Factory Yes 
LiteLLM Yes 
Ludwig Yes 
OpenMetadata Yes 
TrueFoundry Yes 
Vectice Yes 
ZenML Yes 
lakeFS Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

RedBridge Software

Founded

2003

Country

Belgium

Website

www.redbridgesoftware.com

Vendor Details

Company Name

MLflow

Founded

2018

Country

United States

Website

mlflow.org

Product Features

Application Lifecycle Management

Administrator Level Control No 
Defect Tracking Yes 
Iteration Planning No 
Project Management Yes 
Release Management Yes 
Requirements Review No 
Task Management Yes 
Test Case Tracking No 
User Level Management No 
Version Control Yes 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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