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What is Vega-Altair?

The Vega-Altair open-source project functions independently from Altair Engineering, Inc., providing users with an opportunity to concentrate more on understanding their data and its implications. By leveraging Vega-Altair, individuals can utilize a straightforward and consistent API built on the powerful Vega-Lite visualization framework. This elegant simplicity facilitates the generation of visually striking and meaningful graphics with minimal coding required. The core principle involves establishing connections between data columns and visual encoding channels, such as the x-axis, y-axis, and color attributes. As a result, the detailed elements of the plot are handled automatically, ensuring a seamless user experience. Building on this declarative plotting approach, a diverse array of both fundamental and sophisticated visualizations can be constructed using concise grammar, thus accommodating various levels of data presentation. Ultimately, the user-centric design of the Vega-Altair initiative enables individuals to effectively translate complex data insights into compelling visual narratives. This capability not only enhances comprehension but also encourages more informed decision-making based on visualized data.

What is DataMelt?

DataMelt, commonly referred to as "DMelt," is a versatile environment designed for numerical computations, data analysis, data mining, and computational statistics. It facilitates the plotting of functions and datasets in both 2D and 3D, enables statistical testing, and supports various forms of data analysis, numeric computations, and function minimization. Additionally, it is capable of solving linear and differential equations, and provides methods for symbolic, linear, and non-linear regression. The Java API included in DataMelt integrates neural network capabilities alongside various data manipulation techniques utilizing different algorithms. Furthermore, it offers support for symbolic computations through Octave/Matlab programming elements. As a computational environment based on a Java platform, DataMelt is compatible with multiple operating systems and supports various programming languages, distinguishing it from other statistical tools that often restrict users to a single language. This software uniquely combines Java, the most prevalent enterprise language globally, with popular data science scripting languages such as Jython (Python), Groovy, and JRuby, thereby enhancing its versatility and user accessibility. Consequently, DataMelt emerges as an essential tool for researchers and analysts seeking a comprehensive solution for complex data-driven tasks.

Media

Media

Integrations Supported

Python

Integrations Supported

Apache NetBeans
Eclipse BIRT

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

$0
Access to full documentation (examples, Java API documentation, online manual) requires one-time membership payment (20$/user)
Free Version

Supported Platforms

SaaS

Supported Platforms

Android
Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support

Training Options

Documentation Hub

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Vega-Altair

Company Website

altair-viz.github.io

Company Facts

Organization Name

jWork.ORG

Date Founded

2005

Company Location

United States

Company Website

datamelt.org

Categories and Features

Component Libraries

Not specified

Data Visualization

Not specified

Categories and Features

Artificial Intelligence

For Healthcare
Image Recognition
Machine Learning
Natural Language Processing
Predictive Analytics

Data Analysis

Data Discovery
Data Visualization
Predictive Analytics
Regression Analysis
Statistical Modeling
Text Analytics

Data Mining

Data Extraction
Data Visualization
Machine Learning
Predictive Modeling
Statistical Analysis
Text Mining

Data Visualization

Analytics
Simulation Models
Visual Discovery

Deep Learning

Convolutional Neural Networks
Document Classification
ML Algorithm Library
Model Training
Self-Learning
Visualization

Education

Not specified

Neural Network

Not specified

Statistical Analysis

Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Simulation
Survival Analysis
Time Series
Visualization

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