MXNet

MXNet

The Apache Software Foundation
+

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About

ConvNetJS is a Javascript library for training deep learning models (neural networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat. The library allows you to formulate and solve neural networks in Javascript, and was originally written by @karpathy. However, the library has since been extended by contributions from the community and more are warmly welcome. The fastest way to obtain the library in a plug-and-play way if you don't care about developing is through this link to convnet-min.js, which contains the minified library. Alternatively, you can also choose to download the latest release of the library from Github. The file you are probably most interested in is build/convnet-min.js, which contains the entire library. To use it, create a bare-bones index.html file in some folder and copy build/convnet-min.js to the same folder.

About

A hybrid front-end seamlessly transitions between Gluon eager imperative mode and symbolic mode to provide both flexibility and speed. Scalable distributed training and performance optimization in research and production is enabled by the dual parameter server and Horovod support. Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R and Perl. A thriving ecosystem of tools and libraries extends MXNet and enables use-cases in computer vision, NLP, time series and more. Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision-making process have stabilized in a manner consistent with other successful ASF projects. Join the MXNet scientific community to contribute, learn, and get answers to your questions.

About

Zebra by Mipsology is the ideal Deep Learning compute engine for neural network inference. Zebra seamlessly replaces or complements CPUs/GPUs, allowing any neural network to compute faster, with lower power consumption, at a lower cost. Zebra deploys swiftly, seamlessly, and painlessly without knowledge of underlying hardware technology, use of specific compilation tools, or changes to the neural network, the training, the framework, and the application. Zebra computes neural networks at world-class speed, setting a new standard for performance. Zebra runs on highest-throughput boards all the way to the smallest boards. The scaling provides the required throughput, in data centers, at the edge, or in the cloud. Zebra accelerates any neural network, including user-defined neural networks. Zebra processes the same CPU/GPU-based trained neural network with the same accuracy without any change.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers, professionals and researchers seeking a solution for training deep learning models

Audience

Developers and researchers requiring an open-source deep learning framework for research prototyping and production

Audience

Professionals in need of a deep learning compute engine to accelerate their neural network inference anywhere

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

ConvNetJS
cs.stanford.edu/people/karpathy/convnetjs/

Company Information

The Apache Software Foundation
Founded: 1999
United States
mxnet.apache.org

Company Information

Mipsology
United States
mipsology.com

Alternatives

Alternatives

Alternatives

Neural Designer

Neural Designer

Artelnics
Deci

Deci

Deci AI
Caffe

Caffe

BAIR

Categories

Categories

Categories

Integrations

AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon EC2 P4 Instances
Amazon Elastic Inference
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Amazon Web Services (AWS)
Caffe
Cameralyze
Flower
GPUonCLOUD
Google Cloud Deep Learning VM Image
Gradient
Guild AI
Horovod
LeaderGPU
MLReef
NVIDIA Triton Inference Server
Qwen3-Omni

Integrations

AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon EC2 P4 Instances
Amazon Elastic Inference
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Amazon Web Services (AWS)
Caffe
Cameralyze
Flower
GPUonCLOUD
Google Cloud Deep Learning VM Image
Gradient
Guild AI
Horovod
LeaderGPU
MLReef
NVIDIA Triton Inference Server
Qwen3-Omni

Integrations

AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon EC2 P4 Instances
Amazon Elastic Inference
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Amazon Web Services (AWS)
Caffe
Cameralyze
Flower
GPUonCLOUD
Google Cloud Deep Learning VM Image
Gradient
Guild AI
Horovod
LeaderGPU
MLReef
NVIDIA Triton Inference Server
Qwen3-Omni
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