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Deep Learning with JAX
Engelsk
Bogcover for Deep Learning with JAX af Grigory Sapunov, 9781633438880
Specifikationer
Sprog:
Engelsk
Sider:
408
ISBN-13:
9781633438880
Indbinding:
Hardback
ISBN-10:
1633438880
Kategori:
Udg. Dato:
29 okt 2024
Størrelse i cm:
23,4 x 18,8 x 2,7
Oplagsdato:
29 okt 2024
Forfatter(e):

Deep Learning with JAX

Engelsk
Hardback 2024
Format:

Bog beskrivelse

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 your understanding of JAX’s concepts. The engaging examples introduce the fundamental concepts on which JAX relies and then show you how to apply them to real-world tasks. You’ll learn how to use JAX’s ecosystem of high-level libraries and modules, and also how to combine TensorFlow and PyTorch with JAX for data loading and deployment.

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699,01 kr
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90 dages retur
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Specifikationer
Sprog:
Engelsk
Sider:
408
ISBN-13:
9781633438880
Indbinding:
Hardback
ISBN-10:
1633438880
Kategori:
Udg. Dato:
29 okt 2024
Størrelse i cm:
23,4 x 18,8 x 2,7
Oplagsdato:
29 okt 2024
Forfatter(e):
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