Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
Yes
API Access
Has API
No
Integrations
Amdocs Customer Experience Suite
No
Apache Spark
Yes
FreedomFi
No
Hadoop
Yes
k0rdent
No
Integrations
Amdocs Customer Experience Suite
Yes
Apache Spark
No
FreedomFi
Yes
Hadoop
No
k0rdent
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
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
Yes
Live Training (Online)
No
In Person
No
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
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
No