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About

Improve the accuracy of your machine learning models with publicly available datasets. Save time on data discovery and preparation by using curated datasets that are ready to use in machine learning workflows and easy to access from Azure services. Account for real-world factors that can impact business outcomes. By incorporating features from curated datasets into your machine learning models, improve the accuracy of predictions and reduce data preparation time. Share datasets with a growing community of data scientists and developers. Deliver insights at hyperscale using Azure Open Datasets with Azure’s machine learning and data analytics solutions. There's no additional charge for using most Open Datasets. Pay only for Azure services consumed while using Open Datasets, such as virtual machine instances, storage, networking resources, and machine learning. Curated open data made easily accessible on Azure.

About

Labellerr is a data annotation platform designed to expedite the preparation of high-quality labeled datasets for AI and machine learning models. It supports various data types, including images, videos, text, PDFs, and audio, catering to diverse annotation needs. The platform offers automated annotation features, such as model-assisted labeling and active learning, to accelerate the labeling process. Additionally, Labellerr provides advanced analytics and smart quality assurance tools to ensure the accuracy and reliability of annotations. For projects requiring specialized knowledge, Labellerr offers expert-in-the-loop services, including access to professionals in fields like healthcare and automotive.

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

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

Audience

Companies searching for a curated solution to manage and access their open data

Audience

Companies that need a data labeling platform

Support

Phone Support Supported
24/7 Live Support Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Supported

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

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 Supported
Webinars Supported
Live Online Supported
In Person Not Supported

Training

Documentation Not Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Microsoft
Founded: 1975
United States
azure.microsoft.com/en-us/products/open-datasets/

Company Information

Labellerr
Founded: 2022
United States
www.labellerr.com

Alternatives

Alternatives

Ango Hub

Ango Hub

iMerit
DataChain

DataChain

iterative.ai

Categories

AI Development Supported
Data Management Supported
Data Modeling Supported

Categories

AI Fine-Tuning Supported
Data Annotation Supported
Data Labeling Supported
Image Annotation Supported
RLHF Supported
Video Annotation Supported

Integrations

Microsoft Azure Supported

Integrations

Microsoft Azure Not Supported
Claim Azure Open Datasets and update features and information
Claim Azure Open Datasets and update features and information
Claim Labellerr and update features and information
Claim Labellerr and update features and information