Python5.0 out of 5 stars |
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Related Products
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JAX:
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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Python:
About
The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.
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JAX:
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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Python:
Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Supported
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JAX:
Audience
Professional researchers and developers searching for a solution to manage their numerical computing and machine learning operations in Python
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Python:
Audience
Developers interested in a beautiful but advanced programming language
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JAX:
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Python:
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Not Supported
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JAX:
API
Offers API
Supported
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Python:
API
Offers API
Supported
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JAX:
Screenshots and Videos |
Python:
Screenshots and Videos |
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JAX:
Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Python:
Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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JAX:
Reviews/
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Python:
Reviews/
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Python:
Pros & Cons from Real UsersPros
Cons
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JAX:
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Python:
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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JAX:
Company InformationJAX
United States
docs.jax.dev/en/latest/
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Python:
Company InformationPython
Founded: 1991
www.python.org
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JAX:
Alternatives |
Python:
Alternatives |
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Python:
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JAX:
Categories |
Python:
Categories |
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JAX:
Integrations
Flower
Supported
LiteRT
Supported
TensorFlow
Supported
Thunder Compute
Supported
Apache TinkerPop
Not Supported
DebuggAI
Not Supported
FastWebHost
Not Supported
KloudMate
Not Supported
List & Label
Not Supported
MakerSuite
Not Supported
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Python:
Integrations
Flower
Supported
LiteRT
Supported
TensorFlow
Supported
Thunder Compute
Supported
Apache TinkerPop
Supported
DebuggAI
Supported
FastWebHost
Supported
KloudMate
Supported
List & Label
Supported
MakerSuite
Supported
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JAX:
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Python:
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