Deep Learning with JAX

Price: $59.99 – $55.12
(as of Nov 27,2024 18:55:05 UTC – Details)

From the Publisher

Publisher ‏ : ‎ Manning (October 29, 2024)
Language ‏ : ‎ English
Paperback ‏ : ‎ 408 pages
ISBN-10 ‏ : ‎ 1633438880
ISBN-13 ‏ : ‎ 978-1633438880
Item Weight ‏ : ‎ 1.5 pounds
Dimensions ‏ : ‎ 7.38 x 0.9 x 9.25 inches

Deep learning with JAX is a powerful combination that allows for efficient training of neural networks on both CPUs and GPUs. JAX, a numerical computing library, provides a high-performance and composable way to build and train neural networks while leveraging the automatic differentiation capabilities of deep learning frameworks like TensorFlow and PyTorch.

With JAX, developers can take advantage of features such as automatic batching, JIT compilation, and support for vectorized operations to accelerate training and inference tasks. This makes it ideal for training large-scale models on complex datasets.

In addition, JAX supports the use of hardware accelerators like GPUs and TPUs, making it a versatile tool for deep learning projects of all sizes. Its functional programming paradigm allows for easy debugging and experimentation, making it a popular choice among researchers and practitioners in the field.

Overall, deep learning with JAX offers a flexible and efficient approach to building and training neural networks, making it a valuable tool for anyone looking to push the boundaries of AI research and applications.
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