Caffe

Caffe

BAIR
DataMelt

DataMelt

jWork.ORG
+
+

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About

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Check out our web image classification demo! Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices. Extensible code fosters active development. In Caffe’s first year, it has been forked by over 1,000 developers and had many significant changes contributed back. Thanks to these contributors the framework tracks the state-of-the-art in both code and models. Speed makes Caffe perfect for research experiments and industry deployment. Caffe can process over 60M images per day with a single NVIDIA K40 GPU.

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.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

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

Audience

Anyone looking for an open-source deep learning framework with expression, speed and modularity

Audience

scientists, students

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Not Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Supported
Free Trial Not Supported

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

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Supported

Company Information

BAIR
United States
caffe.berkeleyvision.org

Company Information

jWork.ORG
Founded: 2005
United States
datamelt.org

Alternatives

MXNet

MXNet

The Apache Software Foundation

Alternatives

DeepSpeed

DeepSpeed

Microsoft
Statistix

Statistix

Analytical Software
JMP Statistical Software

JMP Statistical Software

JMP Statistical Discovery

Categories

AI Development Supported
Deep Learning Supported
Neural Network Supported

Categories

Data Analysis Supported
Data Mining Supported
Data Visualization Supported
Deep Learning Supported
Education Supported
Neural Network Supported

Deep Learning Features

Convolutional Neural Networks Not Supported
Document Classification Supported
Image Segmentation Not Supported
ML Algorithm Library Not Supported
Model Training Not Supported
Neural Network Modeling Not Supported
Self-Learning Not Supported
Visualization Supported

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

Integrations

AWS Elastic Fabric Adapter (EFA) Supported
AWS Marketplace Supported
Amazon Web Services (AWS) Supported
Apache NetBeans Not Supported
Docker Supported
Eclipse BIRT Not Supported
Fabric for Deep Learning (FfDL) Supported
Lambda Supported
NVIDIA DIGITS Supported
OpenVINO Supported
Polyaxon Supported
Pop!_OS Supported
Zebra by Mipsology Supported

Integrations

AWS Elastic Fabric Adapter (EFA) Not Supported
AWS Marketplace Not Supported
Amazon Web Services (AWS) Not Supported
Apache NetBeans Supported
Docker Not Supported
Eclipse BIRT Supported
Fabric for Deep Learning (FfDL) Not Supported
Lambda Not Supported
NVIDIA DIGITS Not Supported
OpenVINO Not Supported
Polyaxon Not Supported
Pop!_OS Not Supported
Zebra by Mipsology Not Supported
Claim Caffe and update features and information
Claim Caffe and update features and information
Claim DataMelt and update features and information
Claim DataMelt and update features and information