DataMeltjWork.ORG
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MXNetThe Apache Software Foundation
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Related Products
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About
DataMelt (or "DMelt") is an environment for numeric computation, data analysis, data mining, computational statistics, and data visualization. DataMelt can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. Linear, non-linear and symbolic regression are also available. Neural networks and various data-manipulation methods are integrated using Java API. Elements of symbolic computations using Octave/Matlab scripting are supported.
DataMelt is a computational environment for Java platform. It can be used with different programming languages on different operating systems. Unlike other statistical programs, it is not limited to a single programming language. This software combines the world's most-popular enterprise language, Java, with the most popular scripting language used in data science, such as Jython (Python), Groovy, JRuby.
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About
A hybrid front-end seamlessly transitions between Gluon eager imperative mode and symbolic mode to provide both flexibility and speed. Scalable distributed training and performance optimization in research and production is enabled by the dual parameter server and Horovod support. Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R and Perl. A thriving ecosystem of tools and libraries extends MXNet and enables use-cases in computer vision, NLP, time series and more. Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision-making process have stabilized in a manner consistent with other successful ASF projects. Join the MXNet scientific community to contribute, learn, and get answers to your questions.
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Not Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
scientists, students
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Audience
Developers and researchers requiring an open-source deep learning framework for research prototyping and production
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Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Not Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
$0
Access to full documentation (examples, Java API documentation, online manual) requires one-time membership payment (20$/user)
Free Version
Supported
Free Trial
Not Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationjWork.ORG
Founded: 2005
United States
datamelt.org
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Company InformationThe Apache Software Foundation
Founded: 1999
United States
mxnet.apache.org
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Alternatives |
Alternatives |
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Categories |
Categories |
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Deep Learning Features
Convolutional Neural Networks
Supported
Document Classification
Supported
Image Segmentation
Not Supported
ML Algorithm Library
Supported
Model Training
Supported
Neural Network Modeling
Not Supported
Self-Learning
Supported
Visualization
Supported
Artificial Intelligence Features
Chatbot
Not Supported
For eCommerce
Not Supported
For Healthcare
Supported
For Sales
Not Supported
Image Recognition
Supported
Machine Learning
Supported
Multi-Language
Not Supported
Natural Language Processing
Supported
Predictive Analytics
Supported
Process/Workflow Automation
Not Supported
Rules-Based Automation
Not Supported
Virtual Personal Assistant (VPA)
Not Supported
Data Analysis Features
Data Discovery
Supported
Data Visualization
Supported
High Volume Processing
Not Supported
Predictive Analytics
Supported
Regression Analysis
Supported
Sentiment Analysis
Not Supported
Statistical Modeling
Supported
Text Analytics
Supported
Data Mining Features
Data Extraction
Supported
Data Visualization
Supported
Fraud Detection
Not Supported
Linked Data Management
Not Supported
Machine Learning
Supported
Predictive Modeling
Supported
Semantic Search
Not Supported
Statistical Analysis
Supported
Text Mining
Supported
Data Visualization Features
Analytics
Supported
Content Management
Not Supported
Dashboard Creation
Not Supported
Filtered Views
Not Supported
OLAP
Not Supported
Relational Display
Not Supported
Simulation Models
Supported
Visual Discovery
Supported
Statistical Analysis Features
Analytics
Supported
Association Discovery
Supported
Compliance Tracking
Supported
File Management
Supported
File Storage
Supported
Forecasting
Supported
Multivariate Analysis
Supported
Regression Analysis
Supported
Statistical Process Control
Not Supported
Statistical Simulation
Supported
Survival Analysis
Supported
Time Series
Supported
Visualization
Supported
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Integrations
AWS Elastic Fabric Adapter (EFA)
Not Supported
AWS Marketplace
Not Supported
Amazon EC2 Inf1 Instances
Not Supported
Amazon EC2 P4 Instances
Not Supported
Amazon Elastic Inference
Not Supported
Amazon SageMaker Debugger
Not Supported
Amazon SageMaker Model Building
Not Supported
Apache NetBeans
Supported
Cameralyze
Not Supported
Eclipse BIRT
Supported
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Integrations
AWS Elastic Fabric Adapter (EFA)
Supported
AWS Marketplace
Supported
Amazon EC2 Inf1 Instances
Supported
Amazon EC2 P4 Instances
Supported
Amazon Elastic Inference
Supported
Amazon SageMaker Debugger
Supported
Amazon SageMaker Model Building
Supported
Apache NetBeans
Not Supported
Cameralyze
Supported
Eclipse BIRT
Not Supported
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