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- Quickstart — JAX documentation
JAX is a library for array-oriented numerical computation (à la NumPy), with automatic differentiation and JIT compilation to enable high-performance machine learning research This document provides a quick overview of essential JAX features, so you can get started with JAX quickly:
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Jax build with the highest winrate runes and items in every role U GG analyzes millions of LoL matches to give you the best LoL champion build Patch 15 12
- JAX® Mice Services - The Jackson Laboratory
The rigorous attention of the JAX team to mouse health means that you can trust what is entering your laboratory Biospecimens, including tissue from aged mice, are also available Check out our signature portfolios to discover some of JAX’s most impactful collections
- Forum for Discovery - The Jackson Laboratory
Forum for Discovery is JAX's annual summer event that brings together leading researchers focused on genomic solutions for critical health challenges, while also expressing gratitude to those who support these efforts
- Installation — JAX documentation
Using JAX requires installing two packages: jax, which is pure Python and cross-platform, and jaxlib which contains compiled binaries, and requires different builds for different operating systems and accelerators
- Find Mice | Order Lab Mice - The Jackson Laboratory
Search the JAX Repository for a mouse model that recapitulates a human disease or a tool strain to explore intricate biological processes Sort and filter by genotype and phenotype to find your perfect research model
- JAX for Machine Learning: how it works and why learn it
What is Jax? Jax is a Python library designed for high-performance ML research Jax is nothing more than a numerical computing library, just like Numpy, but with some key improvements It was developed by Google and used internally both by Google and Deepmind teams Source: JAX documentation
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