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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. ​

About

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

About

ggplot2 is a system for declaratively creating graphics, based on The Grammar of Graphics. You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details. ggplot2 is now over 10 years old and is used by hundreds of thousands of people to make millions of plots. That means, by-and-large, ggplot2 itself changes relatively little. When we do make changes, they will be generally to add new functions or arguments rather than changing the behavior of existing functions, and if we do make changes to existing behavior we will do them for compelling reasons. If you are new to ggplot2 you are better off starting with a systematic introduction, rather than trying to learn from reading individual documentation pages.

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

Professional researchers and developers searching for a solution to manage their numerical computing and machine learning operations in Python

Audience

Researchers in need of an open source machine learning solution to accelerate research prototyping and production deployment

Audience

Developers searching for a powerful Component Libraries solution

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

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

Review this Software

Reviews/Ratings

Overall 5.0 / 5
ease 1.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

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

JAX
United States
docs.jax.dev/en/latest/

Company Information

PyTorch
Founded: 2016
pytorch.org

Company Information

ggplot2
ggplot2.tidyverse.org

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Orange

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AWS Neuron

Amazon Web Services

Categories

Categories

Categories

Integrations

Amazon EC2 Capacity Blocks for ML
Amazon SageMaker Model Building
Amazon SageMaker Studio Lab
ApertureDB
Apolo
Cerebrium
Cleanlab
Deep Lake
Domino Enterprise MLOps Platform
IBM Distributed AI APIs
Intel Tiber AI Studio
Lightning AI
LiteRT
MLReef
NeevCloud
OpenVINO
PaliGemma 2
Python
Sesterce
Vectice

Integrations

Amazon EC2 Capacity Blocks for ML
Amazon SageMaker Model Building
Amazon SageMaker Studio Lab
ApertureDB
Apolo
Cerebrium
Cleanlab
Deep Lake
Domino Enterprise MLOps Platform
IBM Distributed AI APIs
Intel Tiber AI Studio
Lightning AI
LiteRT
MLReef
NeevCloud
OpenVINO
PaliGemma 2
Python
Sesterce
Vectice

Integrations

Amazon EC2 Capacity Blocks for ML
Amazon SageMaker Model Building
Amazon SageMaker Studio Lab
ApertureDB
Apolo
Cerebrium
Cleanlab
Deep Lake
Domino Enterprise MLOps Platform
IBM Distributed AI APIs
Intel Tiber AI Studio
Lightning AI
LiteRT
MLReef
NeevCloud
OpenVINO
PaliGemma 2
Python
Sesterce
Vectice
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