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.
|
About
The VLFeat open source library implements popular computer vision algorithms specializing in image understanding and local features extraction and matching. Algorithms include Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, large scale SVM training, and many others. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. MatConvNet is a MATLAB toolbox implementing Convolutional Neural Networks (CNNs) for computer vision applications. It is simple, efficient, and can run and learn state-of-the-art CNNs. Many pre-trained CNNs for image classification, segmentation, face recognition, and text detection are available.
|
About
The Microsoft Cognitive Toolkit (CNTK) is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph. CNTK allows the user to easily realize and combine popular model types such as feed-forward DNNs, convolutional neural networks (CNNs) and recurrent neural networks (RNNs/LSTMs). CNTK implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers. CNTK can be included as a library in your Python, C#, or C++ programs, or used as a standalone machine-learning tool through its own model description language (BrainScript). In addition you can use the CNTK model evaluation functionality from your Java programs. CNTK supports 64-bit Linux or 64-bit Windows operating systems. To install you can either choose pre-compiled binary packages, or compile the toolkit from the source provided in GitHub.
|
About
The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.
|
|||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||
Audience
scientists, students
|
Audience
Anyone in need of a deep learning software
|
Audience
Developers and enterprises seeking a toolkit solution designed for commercial-grade distributed deep learning
|
Audience
Developers interested in a beautiful but advanced programming language
|
|||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||
API
Offers API
|
API
Offers API
|
API
Offers API
|
API
Offers API
|
|||
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
|||
Pricing
$0
Free Version
Free Trial
|
Pricing
No information available.
Free Version
Free Trial
|
Pricing
No information available.
Free Version
Free Trial
|
Pricing
Free
Free Version
Free Trial
|
|||
Reviews/
|
Reviews/
|
Reviews/
|
Reviews/
|
|||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||
Company InformationjWork.ORG
Founded: 2005
United States
datamelt.org
|
Company InformationVLFeat
United States
www.vlfeat.org/matconvnet/
|
Company InformationMicrosoft
Founded: 1975
United States
docs.microsoft.com/en-us/cognitive-toolkit/
|
Company InformationPython
Founded: 1991
www.python.org
|
|||
Alternatives |
Alternatives |
Alternatives |
Alternatives |
|||
|
|
|
|||||
|
|
|
|
|
|||
|
|
|
|
||||
|
|
|
|||||
Categories |
Categories |
Categories |
Categories |
|||
Artificial Intelligence Features
Chatbot
For eCommerce
For Healthcare
For Sales
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Data Analysis Features
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Mining Features
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Data Visualization Features
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Deep Learning Features
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Statistical Analysis Features
Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization
|
Deep Learning Features
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
|
Deep Learning Features
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
|
||||
Integrations
Binary Ninja
BioTuring Browser
CodePal
DeepSeek-V3
Dianahost
Django
Eclipse Theia
EditRocket
Flawnter
Flower
|
Integrations
Binary Ninja
BioTuring Browser
CodePal
DeepSeek-V3
Dianahost
Django
Eclipse Theia
EditRocket
Flawnter
Flower
|
Integrations
Binary Ninja
BioTuring Browser
CodePal
DeepSeek-V3
Dianahost
Django
Eclipse Theia
EditRocket
Flawnter
Flower
|
Integrations
Binary Ninja
BioTuring Browser
CodePal
DeepSeek-V3
Dianahost
Django
Eclipse Theia
EditRocket
Flawnter
Flower
|
|||
|
|
|
|
|
