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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.

Description

Luminoth is an open-source framework designed for computer vision applications, currently focusing on object detection but with aspirations to expand its capabilities. As it is in the alpha stage, users should be aware that both internal and external interfaces, including the command line, are subject to change as development progresses. For those interested in utilizing GPU support, it is recommended to install the GPU variant of TensorFlow via pip with the command pip install tensorflow-gpu; alternatively, users can opt for the CPU version by executing pip install tensorflow. Additionally, Luminoth offers the convenience of installing TensorFlow directly by using either pip install luminoth[tf] or pip install luminoth[tf-gpu], depending on the desired TensorFlow version. Overall, Luminoth represents a promising tool in the evolving landscape of computer vision technology.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Google Cloud Platform
TensorFlow
Aporia
Axolotl
Azure Marketplace
Cranium
CrateDB
Dagster
Docker
Flyte
H2O.ai
IBM Databand
LiteLLM
RapidSOS
Robust Intelligence
Superwise
conDati
lakeFS
navio
neptune.ai

Integrations

Google Cloud Platform
TensorFlow
Aporia
Axolotl
Azure Marketplace
Cranium
CrateDB
Dagster
Docker
Flyte
H2O.ai
IBM Databand
LiteLLM
RapidSOS
Robust Intelligence
Superwise
conDati
lakeFS
navio
neptune.ai

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

MLflow

Founded

2018

Country

United States

Website

mlflow.org

Vendor Details

Company Name

luminoth

Website

pypi.org/project/luminoth/

Product Features

Machine Learning

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

Product Features

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