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What is FieldDay?

Step into the thrilling world of AI and Machine Learning with FieldDay, accessible right from your smartphone. We've taken the complex task of constructing machine learning models and transformed it into a fun, interactive experience as simple as snapping a picture. With FieldDay, you have the opportunity to create custom AI applications and effortlessly merge them with your favorite tools, all from the convenience of your mobile device. Just supply FieldDay with examples for it to learn from, and it will assist you in crafting a personalized model that can be seamlessly integrated into your projects or applications. You can delve into an array of applications powered by distinctive FieldDay machine learning models. Our broad selection of integration options and export functionalities ensures that embedding a machine learning model into your chosen platform is a breeze. Furthermore, FieldDay allows you to capture data directly using your phone's camera, and our intuitive interface facilitates easy annotation during data collection, enabling you to swiftly construct a unique dataset. In addition, FieldDay offers the capability to preview and modify your models in real-time, guaranteeing a smooth and productive development journey. This groundbreaking tool empowers users to leverage the potential of AI in unprecedented ways, making it an essential resource for anyone interested in the future of technology.

What is Azure Machine Learning?

Optimize the complete machine learning process from inception to execution. Empower developers and data scientists with a variety of efficient tools to quickly build, train, and deploy machine learning models. Accelerate time-to-market and improve team collaboration through superior MLOps that function similarly to DevOps but focus specifically on machine learning. Encourage innovation on a secure platform that emphasizes responsible machine learning principles. Address the needs of all experience levels by providing both code-centric methods and intuitive drag-and-drop interfaces, in addition to automated machine learning solutions. Utilize robust MLOps features that integrate smoothly with existing DevOps practices, ensuring a comprehensive management of the entire ML lifecycle. Promote responsible practices by guaranteeing model interpretability and fairness, protecting data with differential privacy and confidential computing, while also maintaining a structured oversight of the ML lifecycle through audit trails and datasheets. Moreover, extend exceptional support for a wide range of open-source frameworks and programming languages, such as MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R, facilitating the adoption of best practices in machine learning initiatives. By harnessing these capabilities, organizations can significantly boost their operational efficiency and foster innovation more effectively. This not only enhances productivity but also ensures that teams can navigate the complexities of machine learning with confidence.

Media

Media

Integrations Supported

8th Wall
Swift

Integrations Supported

Azure AI Search
Azure Container Registry
Azure Data Science Virtual Machines
Azure Database for MariaDB
Azure Marketplace
BotCore
Cranium
Evvox
Kedro
MLflow
Microsoft Azure
ModelOp
NVIDIA Triton Inference Server
New Relic
Slingshot
Superwise
Visual Studio Code
Wizata

API Availability

Has API

API Availability

Pricing Information

$19.99 per month
Free Version

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS
iPhone

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

FieldDay

Company Location

United States

Company Website

www.field.day/

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/products/machine-learning/

Categories and Features

AI Development

Not specified

Computer Vision

Not specified

Categories and Features

AI Development

Not specified

AI Governance

Not specified

AI Infrastructure

Not specified

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Machine Learning

Predictive Modeling

ML Model Deployment

Not specified

ML Model Management

Not specified

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