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features
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Description

DL4J leverages state-of-the-art distributed computing frameworks like Apache Spark and Hadoop to enhance the speed of training processes. When utilized with multiple GPUs, its performance matches that of Caffe. Fully open-source under the Apache 2.0 license, the libraries are actively maintained by both the developer community and the Konduit team. Deeplearning4j, which is developed in Java, is compatible with any language that runs on the JVM, including Scala, Clojure, and Kotlin. The core computations are executed using C, C++, and CUDA, while Keras is designated as the Python API. Eclipse Deeplearning4j stands out as the pioneering commercial-grade, open-source, distributed deep-learning library tailored for Java and Scala applications. By integrating with Hadoop and Apache Spark, DL4J effectively introduces artificial intelligence capabilities to business settings, enabling operations on distributed CPUs and GPUs. Training a deep-learning network involves tuning numerous parameters, and we have made efforts to clarify these settings, allowing Deeplearning4j to function as a versatile DIY resource for developers using Java, Scala, Clojure, and Kotlin. With its robust framework, DL4J not only simplifies the deep learning process but also fosters innovation in machine learning across various industries.

Description

A hybrid front-end efficiently switches between Gluon eager imperative mode and symbolic mode, offering both adaptability and speed. The framework supports scalable distributed training and enhances performance optimization for both research and real-world applications through its dual parameter server and Horovod integration. It features deep compatibility with Python and extends support to languages such as Scala, Julia, Clojure, Java, C++, R, and Perl. A rich ecosystem of tools and libraries bolsters MXNet, facilitating a variety of use-cases, including computer vision, natural language processing, time series analysis, and much more. Apache MXNet is currently in the incubation phase at The Apache Software Foundation (ASF), backed by the Apache Incubator. This incubation stage is mandatory for all newly accepted projects until they receive further evaluation to ensure that their infrastructure, communication practices, and decision-making processes align with those of other successful ASF initiatives. By engaging with the MXNet scientific community, individuals can actively contribute, gain knowledge, and find solutions to their inquiries. This collaborative environment fosters innovation and growth, making it an exciting time to be involved with MXNet.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AWS Elastic Fabric Adapter (EFA) No 
AWS Marketplace No 
Amazon EC2 Inf1 Instances No 
Amazon EC2 P4 Instances No 
Amazon Elastic Inference No 
Amazon SageMaker Debugger No 
Amazon SageMaker Model Building No 
Apache Spark Yes 
Cameralyze No 
Flower No 
GPUonCLOUD No 
Google Cloud Deep Learning VM Image No 
Gradient No 
Guild AI No 
Hadoop Yes 
Horovod No 
LeaderGPU No 
MLReef No 
NVIDIA Triton Inference Server No 

Integrations

AWS Elastic Fabric Adapter (EFA) Yes 
AWS Marketplace Yes 
Amazon EC2 Inf1 Instances Yes 
Amazon EC2 P4 Instances Yes 
Amazon Elastic Inference Yes 
Amazon SageMaker Debugger Yes 
Amazon SageMaker Model Building Yes 
Apache Spark No 
Cameralyze Yes 
Flower Yes 
GPUonCLOUD Yes 
Google Cloud Deep Learning VM Image Yes 
Gradient Yes 
Guild AI Yes 
Hadoop No 
Horovod Yes 
LeaderGPU Yes 
MLReef Yes 
NVIDIA Triton Inference Server Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Deeplearning4j

Founded

2019

Country

Japan

Website

deeplearning4j.org

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

mxnet.apache.org

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

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