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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

Communications service providers utilize Magma's open network core solution to facilitate connectivity through LTE, 5G, Wi-Fi, and additional technologies. This solution presents a cost-effective, adaptable, and commercial-grade Evolved Packet Core (EPC). Meta Connectivity actively contributes to the development of Magma, which empowers Communication Service Providers (CSPs) to offer rapid and dependable internet access, enriched with unique features that emerge from a vibrant open-source developer community. Serving as a versatile open-source software platform, Magma allows operators to efficiently establish mobile networks even in remote locations while maintaining a reasonable cost structure. By collaborating with qualified partners for the deployment and management of Magma, CSPs can be confident that their most demanding requirements will be satisfied. Notably, Magma is agnostic to vendors, hardware, and networks, enabling CSPs to select the most suitable options for their needs, ranging from radio access network (RAN) equipment to standard hardware and a variety of licensed or unlicensed spectrum options. This flexibility ensures that service providers can tailor their networks to meet the specific demands of their operational environment and customer base.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amdocs Customer Experience Suite
Apache Spark
FreedomFi
Hadoop
k0rdent

Integrations

Amdocs Customer Experience Suite
Apache Spark
FreedomFi
Hadoop
k0rdent

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Deeplearning4j

Founded

2019

Country

Japan

Website

deeplearning4j.org

Vendor Details

Company Name

Meta Platforms

Country

United States

Website

www.facebook.com/connectivity/solutions/magma

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Product Features

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