ProdigyExplosion
|
||||||
Related Products
|
||||||
About
Radically efficient machine teaching. An annotation tool powered by active learning. Prodigy is a scriptable annotation tool so efficient that data scientists can do the annotation themselves, enabling a new level of rapid iteration. Today’s transfer learning technologies mean you can train production-quality models with very few examples. With Prodigy you can take full advantage of modern machine learning by adopting a more agile approach to data collection. You'll move faster, be more independent and ship far more successful projects. Prodigy brings together state-of-the-art insights from machine learning and user experience. With its continuous active learning system, you're only asked to annotate examples the model does not already know the answer to. The web application is powerful, extensible and follows modern UX principles. The secret is very simple: it's designed to help you focus on one decision at a time and keep you clicking – like Tinder for data.
|
About
Repustate provides world-class AI-powered semantic search, sentiment analysis and text analytics for organizations globally. It gives businesses the capability to decode terabytes of information and discover valuable, actionable, business insights more astutely than ever. From our esteemed clients in the Healthcare industry, to recognised leaders in Education, Banking or Governance, Repustate provides continuous deep dives into complex integrated data across industries.
Our solution drives sentiment analysis and text analytics for social media listening, Voice of Customer (VOC), and video content analysis (VCA) across platforms. It encompasses the plethora of slangs, emojis and acronyms superseding the rules of formal language in social media. Whether it’s data from Youtube, IGTV, Facebook, Twitter or TikTok, or your own customer review forums, employee surveys, or EHRs, you can identify the critical aspects of your business precisely.
|
|||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||||
Audience
Data scientists, AI developers, data labelers
|
Audience
Companies of all sizes in all industries that need a powerful sentiment analysis tool
|
|||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||||
API
Offers API
|
API
Offers API
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
$490 one-time fee
Free Version
Free Trial
|
Pricing
$299 per month
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationExplosion
Founded: 2016
Germany
prodi.gy/
|
Company InformationRepustate
Founded: 2008
Canada
www.repustate.com
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
|
|
||||||
Categories |
Categories |
|||||
Data Labeling Features
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
|
Natural Language Processing Features
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
Data Mining Features
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Social Media Analytics Tools Features
Campaign Analytics
Competitor Monitoring
Customizable Reports
Engagement Tracking
Influencer Tracking
Multi-Channel Data Collection
Text Mining Features
Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering
|
|||||
Integrations
ZenML
|
||||||
|
|
|