Deep Learning With Jax
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Deep Learning with JAX
Author: Grigory Sapunov
language: en
Publisher: Simon and Schuster
Release Date: 2024-10-29
"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" --Publisher's description.
Machine Learning for JAX
Author: GILBERTO. NEAL
language: en
Publisher: Independently Published
Release Date: 2025-02-27
Machine learning is evolving rapidly, and efficiency is more critical than ever. Machine Learning for JAX is your ultimate guide to leveraging JAX for high-performance deep learning, large-scale AI training, and cutting-edge research. Whether you're a researcher, engineer, or AI enthusiast, this book will equip you with the tools to build faster, scalable, and optimized models using JAX's powerful automatic differentiation, JIT compilation, and GPU/TPU acceleration. This book provides comprehensive and hands-on coverage of JAX, from the fundamentals of numerical computing to advanced AI applications, including reinforcement learning, large language models (LLMs), and distributed training. You'll explore real-world industry use cases, optimize AI workflows with pmap and pjit, and learn how to handle massive datasets efficiently. Through detailed explanations, real-world examples, and working code implementations, you'll gain a deep practical understanding of JAX and its role in accelerating machine learning. Each chapter breaks down complex topics in an easy-to-follow manner, ensuring that both beginners and experienced developers can harness the full potential of JAX. What You Will Learn: Fundamentals of JAX and how it differs from NumPy and TensorFlow JIT compilation and vectorization for massive speedups Optimization techniques using SGD, Adam, and RMSprop in JAX Distributed training with multi-GPU and TPU acceleration Building and optimizing large-scale AI models like VAEs, GANs, and LLMs Using JAX in scientific computing and graph neural networks (GNNs) Real-world production use cases and how JAX integrates with Google's AI ecosystem Why This Book? Unlike other deep learning books, Machine Learning for JAX goes beyond the basics and focuses on practical, real-world applications. You won't just learn theory-you'll build, optimize, and scale AI models like a pro. Whether you're working on academic research, AI startups, or enterprise-scale ML systems, this book will elevate your machine learning capabilities. JAX is redefining the future of machine learning and AI research. Don't get left behind. Whether you're an ML researcher, software engineer, or data scientist, this book will empower you with the knowledge and skills to stay ahead in the AI revolution. Get your copy now and unlock the full power of JAX!
Dive Into Deep Learning
The leading experts in system change and learning, with their school-based partners around the world, have created this essential companion to their runaway best-seller, Deep Learning: Engage the World Change the World. This hands-on guide provides a roadmap for building capacity in teachers, schools, districts, and systems to design deep learning, measure progress, and assess conditions needed to activate and sustain innovation. Dive Into Deep Learning: Tools for Engagement is rich with resources educators need to construct and drive meaningful deep learning experiences in order to develop the kind of mindset and know-how that is crucial to becoming a problem-solving change agent in our global society. Designed in full color, this easy-to-use guide is loaded with tools, tips, protocols, and real-world examples. It includes: • A framework for deep learning that provides a pathway to develop the six global competencies needed to flourish in a complex world — character, citizenship, collaboration, communication, creativity, and critical thinking. • Learning progressions to help educators analyze student work and measure progress. • Learning design rubrics, templates and examples for incorporating the four elements of learning design: learning partnerships, pedagogical practices, learning environments, and leveraging digital. • Conditions rubrics, teacher self-assessment tools, and planning guides to help educators build, mobilize, and sustain deep learning in schools and districts. Learn about, improve, and expand your world of learning. Put the joy back into learning for students and adults alike. Dive into deep learning to create learning experiences that give purpose, unleash student potential, and transform not only learning, but life itself.