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Deep Learning with JAX

manning publications

Deep Learning with JAX

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Accelerate deep learning and other number-intensive tasks with JAX, Google’s awesome high-performance numerical computing library. In Deep Learning with JAX you will learn how to: Use JAX for numerical calculations Build differentiable models with JAX primitives Run distributed and parallelized computations with JAX Use high-level neural network libraries such as Flax and Haiku Leverage libraries and modules from the JAX ecosystem The JAX numerical computing library tackles the core performance challenges at the heart of deep learning and other scientific computing tasks. By combining Google’s Accelerated Linear Algebra platform (XLA) with a hyper-optimized version of NumPy and a variety of other high-performance features, JAX delivers a huge performance boost in low-level computations and transformations. Deep Learning with JAX is a hands-on guide to using JAX for deep learning and other mathematically-intensive applications. Google Developer Expert Grigory Sapunov steadily builds

Brändi
manning publications
EAN / GTIN
9781633438880