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Key benefits

Understand how to use PyTorch to build advanced neural network models

Get the best from PyTorch by working with Hugging Face, fastai, PyTorch Lightning, PyTorch Geometric, Flask, and Docker

Unlock faster training with multiple GPUs and optimize model deployment using efficient inference frameworks

Description

PyTorch is making it easier than ever before for anyone to build deep learning applications. This PyTorch deep learning book will help you uncover expert techniques to get the most out of your data and build complex neural network models. You’ll build convolutional neural networks for image classification and recurrent neural networks and transformers for sentiment analysis. As you advance, you'll apply deep learning across different domains, such as music, text, and image generation, using generative models, including diffusion models. You'll not only build and train your own deep reinforcement learning models in PyTorch but also learn to optimize model training using multiple CPUs, GPUs, and mixed-precision training. You’ll deploy PyTorch models to production, including mobile devices. Finally, you’ll discover the PyTorch ecosystem and its rich set of libraries. These libraries will add another set of tools to your deep learning toolbelt, teaching you how to use fastai to prototype models and PyTorch Lightning to train models. You’ll discover libraries for AutoML and explainable AI (XAI), create recommendation systems, and build language and vision transformers with Hugging Face. By the end of this book, you'll be able to perform complex deep learning tasks using PyTorch to build smart artificial intelligence models.

Who is this book for?

This deep learning with PyTorch book is for data scientists, machine learning engineers, machine learning researchers, and deep learning practitioners looking to implement advanced deep learning models using PyTorch. This book is ideal for those looking to switch from TensorFlow to PyTorch. Working knowledge of deep learning with Python is required.

What you will learn

Implement text, vision, and music generation models using PyTorch

Build a deep Q-network (DQN) model in PyTorch

Deploy PyTorch models on mobile devices (Android and iOS)

Become well versed in rapid prototyping using PyTorch with fastai

Perform neural architecture search effectively using AutoML

Easily interpret machine learning models using Captum

Design ResNets, LSTMs, and graph neural networks (GNNs)

Create language and vision transformer models using Hugging Face

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Machine Learning with PyTorch and Scikit-Learn

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Amazon verified reviews

Kelsey S. Jul 27, 2024

I've been working with PyTorch for a while now, but I really feel like this book took my skills to the next level. The explanations are clear and concise, and the code examples really helped me to understand the concepts. I especially appreciated the coverage of advanced techniques like generative models and graph neural networks, but most of the content is also completely suitable for beginners. I appreciate that the author also focuses on the modern landscape, including how to transition from TensorFlow to PyTorch, coverage of LLMs, neural networks in mobile settings (eg quantized models), autoML, integration with Hugging Face and beyond. I've already used some of the techniques from the book in my own work, and I'm really excited to see what else I can accomplish with PyTorch. Overall, I highly recommend this book to anyone who wants to learn more about PyTorch and deep learning.

Amazon Verified review

misagh bahramipoor Jul 14, 2024

Mastering PyTorch stands out as an essential resource for both aspiring and seasoned machine learning engineers looking to stay abreast of the latest developments in deep learning. Its comprehensive approach, practical focus, and timely coverage of emerging trends make it a must-read for professionals aiming to master PyTorch and apply it effectively in diverse domains. Whether you’re developing CNNs for image recognition, fine-tuning large language models, or exploring the frontiers of generative and multimodal learning, this book offers invaluable guidance and insights.

Sharad Joshi Jun 19, 2024

This is one of the best books to practically learn PyTorch. It strikes a great balance between code and theory, covering all major algorithms and giving you a solid tour of the ML/AI world up to early 2024.

Ahmed Ahres Jun 08, 2024

I've been reading "Mastering PyTorch" and I'm blown away by the depth and breadth of knowledge shared by the author. As an AI enthusiast myself, I was looking for a book that would take my skills to the next level, and this book absolutely delivered.The author's expertise in PyTorch and AI shines through on every page. The book is meticulously organized, with each chapter building upon the previous one to create a cohesive and comprehensive learning experience. The writing is clear, concise, and engaging, making even the most complex concepts accessible to readers with varying levels of experience.I truly loved the focus on practical applications and real-world examples. The author doesn't just explain the theory behind PyTorch and AI; they show you how to implement models, optimize training, and deploy them to production. The chapters on generative models, reinforcement learning, and transformers are particularly impressive, providing a level of detail and insight that's hard to find elsewhere.The book's coverage of the PyTorch ecosystem is also noteworthy, with in-depth explorations of fastai, PyTorch Lightning, and Hugging Face. The author's enthusiasm for these tools is infectious, and I found myself excited to try out new libraries and techniques (would highly recommend looking at Hugging Face!).In short, "Mastering PyTorch" is an essential resource for anyone looking to take their AI and LLM skills to the next level. Whether you're a beginner or an experienced developer, this book definitely has something to offer! The author's passion for PyTorch and AI is evident on every page, and their expertise is generously shared with the reader.If you're serious about mastering PyTorch and building complex AI models, you should definitely consider reading this book!

Saurav R Jul 10, 2024

"Mastering PyTorch - Second Edition" by Ashish Ranjan Jha is an exceptional resource for both beginners and advanced practitioners in deep learning. The book covers a wide range of topics, from CNNs to multimodal models and LLMs, providing clear and comprehensive explanations. The practical examples and hands-on approach make it easy to apply the concepts. Highly recommended for anyone looking to deepen their understanding of PyTorch and its applications in AI.

Mastering PyTorch: Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond , Second Edition

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