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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Apache Geronimo is a collection of open-source initiatives aimed at delivering JavaEE/JakartaEE libraries along with Microprofile implementations. Our focus is on creating reusable Java EE components that are both widely utilized and actively maintained. The project supplies libraries that align with the specifications of Java EE and Jakarta EE, while also emphasizing the provision of OSGi bundle metadata. A key objective of the XBean project is to develop a server that operates in a plugin-based manner, similar to how Eclipse functions as a plugin-centric IDE. XBean will have the capability to identify, download, and install server plugins from a repository available on the Internet. Furthermore, it encompasses support for various IoC systems, the option to run without an IoC system, JMX functionality without the need for JMX code, lifecycle and class loader management, and robust integration with Spring. In addition to these features, Apache Geronimo also supports several Microprofile implementations. Moreover, the Apache Geronimo Arthur initiative aims to create a lightweight layer that operates on top of Oracle GraalVM, enhancing the project's versatility and performance. This makes Apache Geronimo a valuable resource for developers seeking comprehensive solutions in the Java ecosystem.

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.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Apache Spark No 
Apache TomEE Yes 
Hadoop No 
Maven Yes 
MyEclipse Yes 

Integrations

Apache Spark Yes 
Apache TomEE No 
Hadoop Yes 
Maven No 
MyEclipse No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

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

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

Apache

Country

United States

Website

geronimo.apache.org

Vendor Details

Company Name

Deeplearning4j

Founded

2019

Country

Japan

Website

deeplearning4j.org

Product Features

Application Server

Admin Console No 
Alerts / Notifications No 
Application Security No 
Multi-Application Support No 
Multiple Environment Support No 
Open Standards Compliance No 
Reporting / Analytics No 
User Management 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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