MXNetThe Apache Software Foundation
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Related Products
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About
JAX is a Python library designed for high-performance numerical computing and machine learning research. It offers a NumPy-like API, facilitating seamless adoption for those familiar with NumPy. Key features of JAX include automatic differentiation, just-in-time compilation, vectorization, and parallelization, all optimized for execution on CPUs, GPUs, and TPUs. These capabilities enable efficient computation for complex mathematical functions and large-scale machine-learning models. JAX also integrates with various libraries within its ecosystem, such as Flax for neural networks and Optax for optimization tasks. Comprehensive documentation, including tutorials and user guides, is available to assist users in leveraging JAX's full potential.
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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.
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Not Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Professional researchers and developers searching for a solution to manage their numerical computing and machine learning operations in Python
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Audience
Developers and researchers requiring an open-source deep learning framework for research prototyping and production
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationJAX
United States
docs.jax.dev/en/latest/
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Company InformationThe Apache Software Foundation
Founded: 1999
United States
mxnet.apache.org
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Categories |
Categories |
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Integrations
Flower
Supported
AWS EC2 Trn3 Instances
Supported
AWS Marketplace
Not Supported
Amazon EC2 Inf1 Instances
Not Supported
Amazon EC2 P4 Instances
Not Supported
Amazon Elastic Inference
Not Supported
Amazon SageMaker Model Building
Not Supported
Cameralyze
Not Supported
Google Cloud Deep Learning VM Image
Not Supported
Gradient
Not Supported
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Integrations
Flower
Supported
AWS EC2 Trn3 Instances
Not Supported
AWS Marketplace
Supported
Amazon EC2 Inf1 Instances
Supported
Amazon EC2 P4 Instances
Supported
Amazon Elastic Inference
Supported
Amazon SageMaker Model Building
Supported
Cameralyze
Supported
Google Cloud Deep Learning VM Image
Supported
Gradient
Supported
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