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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.

What is Autoplot?

Autoplot is an all-encompassing workspace tailored for macOS that seamlessly integrates the processes of importing, analyzing, visualizing, annotating, and publishing scientific data, thereby removing the hassle of repetitive copy-and-paste tasks typically required when using various applications like chatbots, terminal interfaces, and image editing programs. Users can effortlessly import files from both local sources and SFTP, define delimiters, headers, and encoding formats, merge multiple files into one project, and apply Python scripts provided by an assistant for tasks such as filtering, splicing, or generating derived variables. Among its extensive features, pre-approved analysis cards encompass a diverse array of statistical techniques including CCDF, AUC, log-binned distributions, power-law and truncated fits, as well as diagnostics for Xmin, finite-size scaling, scaling relations, and correlation matrices and networks, while users also have the liberty to design custom statistics to be executed within the embedded Python environment. The outputs generated in Autoplot can be reused, allowing them to be replotted, refitted, layered, composed, or exported as required without needing to rebuild the workflow from the beginning. Additionally, Autoplot offers a wide range of visualization options, such as X&Y plots, histograms, heat maps, categorical charts, and 3D representations including scatter, surface, and line plots, while also enabling the addition of unlimited overlays, fits, and contours, ensuring users have a flexible toolkit for their scientific data requirements. With its intuitive interface and robust functionalities, Autoplot emerges as an indispensable resource for researchers and scientists across various disciplines, fostering a more efficient approach to data management and analysis. As the demand for streamlined scientific workflows continues to grow, tools like Autoplot are paving the way for innovative research methodologies.

Media

Media

Integrations Supported

Apache NetBeans
Eclipse BIRT
Python

Integrations Supported

Apache NetBeans
Eclipse BIRT
Python

API Availability

Has API

API Availability

Has API

Pricing Information

$0
Free Trial Offered?
Free Version

Pricing Information

$7.99 per month
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

jWork.ORG

Date Founded

2005

Company Location

United States

Company Website

datamelt.org

Company Facts

Organization Name

Autoplot

Company Location

Spain

Company Website

autoplot.ai/

Categories and Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

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

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Statistical Analysis

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

Categories and Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

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Popular Alternatives

No Alternatives
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