Related Products
|
||||||
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
DL4J takes advantage of the latest distributed computing frameworks including Apache Spark and Hadoop to accelerate training. On multi-GPUs, it is equal to Caffe in performance. The libraries are completely open-source, Apache 2.0, and maintained by the developer community and Konduit team. Deeplearning4j is written in Java and is compatible with any JVM language, such as Scala, Clojure, or Kotlin. The underlying computations are written in C, C++, and Cuda. Keras will serve as the Python API. Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs. There are a lot of parameters to adjust when you're training a deep-learning network. We've done our best to explain them, so that Deeplearning4j can serve as a DIY tool for Java, Scala, Clojure, and Kotlin programmers.
|
About
LaunchDarkly feature management platform. Dynamically control the availability of application features to your users. Modern development and operations teams are using feature management to deliver faster and take on more development cycles. This best practice enables engineering teams of any size to continuously deploy code, and empowers business teams with control over features so they can manage their customers' experience. With the LaunchDarkly Feature Management Platform, leading teams are able to reduce risk and launch their ideas at inception. Speed up the pace of software delivery by separating code deployments from feature releases. Deploy when you want, release when you’re ready. Lower the cost of being wrong by using feature flags to rollout new features and services or when migrating systems. Monitor and manage your features in real-time. Test robust functionality instead of just cosmetic changes.
|
||||
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
Anyone looking for an open-source deep learning framework with expression, speed and modularity
|
Audience
Researchers, developers and professionals requiring an open-source, distributed, deep learning library for the JVM
|
Audience
DevOps and IT teams looking for a private registry solution to detect vulnerabilities in images
|
||||
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
|
||||
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
||||
Pricing
No information available.
Free Version
Free Trial
|
Pricing
No information available.
Free Version
Free Trial
|
Pricing
$12 per month
Free Version
Free Trial
|
||||
Reviews/
|
Reviews/
|
Reviews/
|
||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
||||
Company InformationBAIR
United States
caffe.berkeleyvision.org
|
Company InformationDeeplearning4j
Founded: 2019
Japan
deeplearning4j.org
|
Company InformationLaunchDarkly
Founded: 2013
United States
launchdarkly.com
|
||||
Alternatives |
Alternatives |
Alternatives |
||||
|
|
|
|||||
|
|
||||||
|
|
||||||
|
|
|
|||||
Categories |
Categories |
Categories |
||||
Deep Learning Features
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
|
||||||
Integrations
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Activeeon ProActive
Amazon Web Services (AWS)
Azure DevOps Labs
Blink
Comprehensive
Docker
Dynatrace
Easyflow
|
Integrations
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Activeeon ProActive
Amazon Web Services (AWS)
Azure DevOps Labs
Blink
Comprehensive
Docker
Dynatrace
Easyflow
|
Integrations
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Activeeon ProActive
Amazon Web Services (AWS)
Azure DevOps Labs
Blink
Comprehensive
Docker
Dynatrace
Easyflow
|
||||
|
|
|
|