Название: JAX in Action (MEAP v3) Автор: Grigory Sapunov Издательство: Manning Publications Год: 2022 Страниц: 147 Язык: английский Формат: pdf (true) Размер: MB
Accelerate deep learning and other number-intensive tasks with JAX, Google’s awesome high-performance numerical computing library.
In JAX in Action 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.
JAX in Action 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. about the technology
The JAX Python mathematics library is used by many successful deep learning organizations, including Google’s groundbreaking DeepMind team. This exciting newcomer already boasts an amazing ecosystem of tools including high-level deep learning libraries Flax by Google, Haiku by DeepMind, gradient processing and optimization libraries, libraries for evolutionary computations, federated learning, and much more! JAX brings a functional programming mindset to Python deep learning, letting you improve your composability and parallelization in a cluster.
about the book: JAX in Action teaches you how to use JAX and its ecosystem to build neural networks. You’ll learn by exploring interesting examples including an image classification tool, an image filter application, and a massive scale neural network with distributed training across a cluster of TPUs. Discover how to work with JAX for hardware and other low-level aspects and how to solve common machine learning problems with JAX. By the time you’re finished with this awesome book, you’ll be ready to start applying JAX to your own research and prototyping!
High Performance Python for Data Analytics (MEAP) Название: High Performance Python for Data Analytics (MEAP) Автор: Tiago Rodrigues Antao Издательство: Manning Publications Год: 2020 Формат: PDF...
Apache Pulsar in Action (MEAP) Название: Apache Pulsar in Action (MEAP Version 4) Автор: David Kjerrumgaard Издательство: Manning Publications Год: 2020 Формат: true pdf/epub...
Deep Learning for Numerical Applications with SAS Название: Deep Learning for Numerical Applications with SAS Автор: Henry Bequet Издательство: SAS Institute Год: 2018 Страниц: 234 Формат: True PDF,...
Introduction to Computational Models with Python Название: Introduction to Computational Models with Python Автор: Jose M. Garrido Издательство: CRC Год: 2015 Страниц: 496 Формат: PDF Размер: 10 Mb...
Информация
Посетители, находящиеся в группе Гости, не могут оставлять комментарии к данной публикации.