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Average Ratings 0 Ratings

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ease
features
design
support

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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.

Description

Effortlessly switch between eager and graph modes using TorchScript, while accelerating your journey to production with TorchServe. The torch-distributed backend facilitates scalable distributed training and enhances performance optimization for both research and production environments. A comprehensive suite of tools and libraries enriches the PyTorch ecosystem, supporting development across fields like computer vision and natural language processing. Additionally, PyTorch is compatible with major cloud platforms, simplifying development processes and enabling seamless scaling. You can easily choose your preferences and execute the installation command. The stable version signifies the most recently tested and endorsed iteration of PyTorch, which is typically adequate for a broad range of users. For those seeking the cutting-edge, a preview is offered, featuring the latest nightly builds of version 1.10, although these may not be fully tested or supported. It is crucial to verify that you meet all prerequisites, such as having numpy installed, based on your selected package manager. Anaconda is highly recommended as the package manager of choice, as it effectively installs all necessary dependencies, ensuring a smooth installation experience for users. This comprehensive approach not only enhances productivity but also ensures a robust foundation for development.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

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 
Cameralyze Yes 
Flower Yes 
GPUonCLOUD Yes 
Google Cloud Deep Learning VM Image Yes 
Gradient Yes 
Guild AI Yes 
Horovod Yes 
MLReef Yes 
NVIDIA Triton Inference Server Yes 
Amazon EC2 Trn1 Instances No 
GPUEater No 
Voxel51 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 
Cameralyze Yes 
Flower Yes 
GPUonCLOUD Yes 
Google Cloud Deep Learning VM Image Yes 
Gradient Yes 
Guild AI Yes 
Horovod Yes 
MLReef Yes 
NVIDIA Triton Inference Server Yes 
Amazon EC2 Trn1 Instances Yes 
GPUEater Yes 
Voxel51 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 Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App Yes 
iPad App Yes 
Android App Yes 
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 Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

mxnet.apache.org

Vendor Details

Company Name

PyTorch

Founded

2016

Website

pytorch.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

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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