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Average Ratings 0 Ratings

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ease
features
design
support

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Description

AMPL stands out as a robust and user-friendly modeling language tailored for the representation and resolution of intricate optimization challenges. It allows users to create mathematical models using a syntax that closely resembles algebraic notation, making it easier to clearly articulate variables, objectives, and constraints in a concise format. This versatile tool accommodates a diverse array of problem types, such as linear programming, nonlinear programming, and mixed-integer programming, among others. A notable advantage of AMPL is its capability to decouple models from their data, which enhances flexibility and scalability when dealing with extensive problems. The platform seamlessly integrates with a variety of solvers, both commercial and open-source, granting users the liberty to select the most suitable solver tailored to their specific requirements. AMPL operates across various operating systems, including Windows, macOS, and Linux, and provides a range of licensing options to accommodate different user preferences. Furthermore, its intuitive design and comprehensive documentation make it accessible even for those who are new to optimization modeling.

Description

DataMelt, or "DMelt", is an environment for numeric computations, data analysis, data mining and computational statistics. DataMelt allows you to plot functions and data in 2D or 3D, perform statistical testing, data mining, data analysis, numeric computations and function minimization. It also solves systems of linear and differential equations. There are also options for symbolic, non-linear, and linear regression. Java API integrates neural networks and data-manipulation techniques using various data-manipulation algorithms. Support is provided for elements of symbolic computations using Octave/Matlab programming. DataMelt provides a Java platform-based computational environment. It can be used on different operating systems and programming languages. It is not limited to one programming language, unlike other statistical programs. This software combines Java, the most widely used enterprise language in the world, with the most popular data science scripting languages, Jython (Python), Groovy and JRuby.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache NetBeans
Artelys Knitro
Eclipse BIRT
Python

Integrations

Apache NetBeans
Artelys Knitro
Eclipse BIRT
Python

Pricing Details

$3,000 per year
Free Trial
Free Version

Pricing Details

$0
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

AMPL

Founded

2002

Country

United States

Website

ampl.com/products/ampl/

Vendor Details

Company Name

jWork.ORG

Founded

2005

Country

United States

Website

datamelt.org

Product Features

Product 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

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