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Description
Utilize open-source machine learning tools and data visualization techniques to create dynamic data analysis workflows in a visual format, supported by a broad and varied collection of resources. Conduct straightforward data assessments accompanied by insightful visual representations, and investigate statistical distributions through box plots and scatter plots; for more complex inquiries, utilize decision trees, hierarchical clustering, heatmaps, multidimensional scaling, and linear projections. Even intricate multidimensional datasets can be effectively represented in 2D, particularly through smart attribute selection and ranking methods. Engage in interactive data exploration for swift qualitative analysis, enhanced by clear visual displays. The user-friendly graphic interface enables a focus on exploratory data analysis rather than programming, while intelligent defaults facilitate quick prototyping of data workflows. Simply position widgets on your canvas, link them together, import your datasets, and extract valuable insights! When it comes to teaching data mining concepts, we prefer to demonstrate rather than merely describe, and Orange excels in making this approach effective and engaging. The platform not only simplifies the process but also enriches the learning experience for users at all levels.
Description
RAWGraphs is a community-driven project that draws inspiration from various open-source initiatives. It offers nearly 30 distinct visual models designed to help users analyze quantities, hierarchies, and time series to uncover valuable insights from their data. While RAWGraphs operates as a web application, all data processing occurs locally within your browser, ensuring privacy and security. Users can conveniently save their creations or export them in vector or raster formats for further editing in preferred graphic design software. Originally designed for designers and data visualization enthusiasts, RAWGraphs seeks to bridge the gap between spreadsheet tools like Microsoft Excel and vector editing programs such as Adobe Illustrator. This open-source framework was created to simplify the visual representation of complex datasets for users of all skill levels. The project is maintained by a dedicated team comprising DensityDesign, Calibro, and Inmagik, who have been collaborating since 2019 to enhance its features and usability. Additionally, the platform encourages continuous input and contributions from the broader community to foster innovation and improvement.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
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
University of Ljubljana
Country
Slovenia
Website
orange.biolab.si
Vendor Details
Company Name
DensityDesign
Country
United States
Website
rawgraphs.io
Product Features
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Product Features
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery