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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Enhance the efficiency of your deep learning projects and reduce the time it takes to realize value through AI model training and inference. As technology continues to improve in areas like computation, algorithms, and data accessibility, more businesses are embracing deep learning to derive and expand insights in fields such as speech recognition, natural language processing, and image classification. This powerful technology is capable of analyzing text, images, audio, and video on a large scale, allowing for the generation of patterns used in recommendation systems, sentiment analysis, financial risk assessments, and anomaly detection. The significant computational resources needed to handle neural networks stem from their complexity, including multiple layers and substantial training data requirements. Additionally, organizations face challenges in demonstrating the effectiveness of deep learning initiatives that are executed in isolation, which can hinder broader adoption and integration. The shift towards more collaborative approaches may help mitigate these issues and enhance the overall impact of deep learning strategies within companies.

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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AUSIS
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Activeeon ProActive
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon Elastic Inference
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Cameralyze
Flower
GPUonCLOUD
Google Cloud Deep Learning VM Image
Gradient
Guild AI
Horovod
IBM Intelligent Video Analytics
LeaderGPU
MLReef
NVIDIA Triton Inference Server

Integrations

AUSIS
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Activeeon ProActive
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon Elastic Inference
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Cameralyze
Flower
GPUonCLOUD
Google Cloud Deep Learning VM Image
Gradient
Guild AI
Horovod
IBM Intelligent Video Analytics
LeaderGPU
MLReef
NVIDIA Triton Inference Server

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

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/deep-learning-platform

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

mxnet.apache.org

Product Features

Deep Learning

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

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Deep Learning

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

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