Jax.dev
JAX: High performance array computing — JAX documentation
JAX offers Python tools for high-performance array computing, making it easy to build, transform, and optimize machine learning and numerical programs.
Accelerate Python machine learning with JAX
JAX is a Python library focused on high-performance numerical computing, especially for machine learning and scientific applications. On this documentation site, you can learn how to use JAX to speed up array computations, leverage hardware accelerators, and transform your Python programs for research or production.
The site provides clear guides, tutorials, and in-depth concepts to help you get started and master JAX’s features, like just-in-time compilation, automatic differentiation, and vectorization. Whether you’re new to JAX or an experienced developer, you’ll find practical examples and explanations to support your work.
If you’re working on large-scale machine learning or need fast, flexible numerical tools, this documentation is your go-to resource for understanding and using JAX effectively.
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