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Description
Revolutionary machine teaching is here with an exceptionally efficient annotation tool driven by active learning. Prodigy serves as a customizable annotation platform so effective that data scientists can handle the annotation process themselves, paving the way for rapid iteration. The advancements in today's transfer learning technologies allow for the training of high-quality models using minimal examples. By utilizing Prodigy, you can fully leverage contemporary machine learning techniques, embracing a more flexible method for data gathering. This will enable you to accelerate your workflow, gain greater autonomy, and deliver significantly more successful projects. Prodigy merges cutting-edge insights from the realms of machine learning and user experience design. Its ongoing active learning framework ensures that you only need to annotate those examples the model is uncertain about. The web application is not only powerful and extensible but also adheres to the latest user experience standards. The brilliance lies in its straightforward design: it encourages you to concentrate on one decision at a time, keeping you actively engaged – akin to a swipe-right approach for data. Additionally, this streamlined process fosters a more enjoyable and effective annotation experience overall.
Description
The Rinalogy Classification API offers a flexible machine learning solution that seamlessly integrates into your existing application while allowing you to operate within your own infrastructure. In contrast to traditional cloud-based machine learning APIs that necessitate data transfer and operate in an external environment, Rinalogy allows for deployment within your IT framework, ensuring data security and compliance as it works behind your firewall. This API utilizes Exhaustive Sequential Classification, systematically applying models to every document within a dataset. The models generated can be enhanced with additional training data or leveraged for predicting outcomes on new documents at a later time. With its ability to scale through cluster deployment, you can modify the number of workers based on your current workload needs. Furthermore, the Rinalogy API empowers client applications by incorporating features such as text classification, enhanced search capabilities, and personalized recommendations, providing a comprehensive toolkit for data-driven decision-making. This versatility makes it an appealing choice for organizations aiming to optimize their machine learning processes while maintaining control over their data.
API Access
Has API
API Access
Has API
Integrations
ZenML
Pricing Details
$490 one-time fee
Free Trial
Free Version
Pricing Details
No price information available.
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
Explosion
Founded
2016
Country
Germany
Website
prodi.gy/
Vendor Details
Company Name
RINA Systems
Country
United States
Website
www.rinasystems.com/product/rinalogy-api.html
Product Features
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
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Natural Language Processing
Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization
Product Features
Natural Language Processing
Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization