PyTorch

Independently published, 2024. — 540 p. — ISBN: 979-8329915327, ASIN B0D8JKJR9Y. Embark on an enlightening journey through the world of machine learning and artificial intelligence with our comprehensive guide to PyTorch. As one of the premier frameworks in the field, PyTorch has rapidly gained traction among researchers, developers, and enthusiasts alike, owing to its...

Packt Publishing, 2024. — 230 p. Key Features: Reduce the model-building time by applying optimization techniques and approaches. Harness the computing power of multiple devices and machines to boost the training process. Focus on model quality by quickly evaluating different model configurations. Book Description: Penned by an expert in High-Performance Computing (HPC) with...

Second Edition. Packt Publishing, 2024. — 606 p. (converted to PDF). Key Features: Understand the inner workings of various neural network architectures and their implementation, including image classification, object detection, segmentation, generative adversarial networks, transformers, and diffusion models. Build solutions for real-world computer vision problems using...

2nd. ed. - Birmingham: Packt Publishing, 2025. - 448 p. - ISBN: 1835884458. Master GenAI techniques to create images and text using variational autoencoders (VAEs), generative adversarial networks (GANs), LSTMs, and large language models (LLMs). Key Features Implement real-world applications of LLMs and generative AI. Fine-tune models with PEFT and LoRA to speed up training....

Independently published, 2021. — 1187 p. Version 1.0, 2021-05-18 If you're looking for a book where you can learn about Deep Learning and PyTorch without having to spend hours deciphering cryptic text and code, and that's easy and enjoyable to read, this is it :-) The book covers from the basics of gradient descent all the way up to fine-tuning large NLP models (BERT and GPT-2)...

Leanpub, 2022. — 1042 p. 2022-02-12 (v1.1.1). If you're looking for a book where you can learn about Deep Learning and PyTorch without having to spend hours deciphering cryptic text and code, and that's easy and enjoyable to read, this is it :-) PyTorch is the fastest-growing framework for developing deep learning models and it has a huge ecosystem. That is, there are many...

Leanpub, — 2024. — 1047 p. — Version 1.2. — ISBN-13 979-8533935746. If you're looking for a book where you can learn about Deep Learning and PyTorch without having to spend hours deciphering cryptic text and code, and that's easy and enjoyable to read, this is it:-). The book covers the basics of gradient descent up to fine-tuning large NLP models (BERT and GPT-2) using...

O’Reilly Media, Inc., 2020. — 624 p. — ISBN: 978-1492045526. Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first...

Amazon Digital Services LLC, 2019. — 120 p. his book is an exploration of deep learning in Python using PyTorch. The author guides you on how to create neural network models using PyTorch in Python. You will know the initial steps of getting started with PyTorch in Python. This involves installing PyTorch and writing your first code. PyTorch works using the concept of graphs....

Packt Publishing, 2021. — 450 p. — ISBN: 9781789614381. Master advanced techniques and algorithms for deep learning with PyTorch using real-world examples. Key Features Understand how to use PyTorch 1.x to build advanced neural network models. Learn to perform a wide range of tasks by implementing deep learning algorithms and techniques. Gain expertise in domains such as...

Packt, 2024. — 535 p. — Second Edition. Master advanced techniques and algorithms for machine learning with PyTorch using real-world examples. Updated for PyTorch 2.x, including integration with Hugging Face, mobile deployment, diffusion models, and graph neural networks. Key Features: Understand how to use PyTorch to build advanced neural network models. Get the best from...

Apress, 2022. — 240 p. Design and develop end-to-end, production-grade computer vision projects for real-world industry problems. This book discusses computer vision algorithms and their applications using PyTorch. The book begins with the fundamentals of computer vision: convolutional neural nets, RESNET, YOLO, data augmentation, and other regularization techniques used in the...

Manning Publications, 2024. - 432 p. - ISBN: 1633436462. Create your generative AI models for text, images, music, and more! Generative AI tools like ChatGPT, Bard, and DALL-E have transformed the way we work. Learn Generative AI with PyTorch takes you on an incredible hands-on journey through creating and training AI models using Python, the free PyTorch framework, and the...

Independently published, 2025. — 255 p. Harness the Power of PyTorch for Cutting-Edge AI Solutions. PyTorch has become the go-to Deep Learning framework for researchers and industry professionals alike. Whether you're a data scientist, AI engineer, or Python enthusiast, this book will help you master PyTorch and apply it to real-world Machine Learning and Deep Learning...

2nd Edition. — Apress, 2023. — 266 p. — eBook ISBN: 978-1-4842-8925-9. Learn how to use PyTorch to build neural network models using code snippets updated for this second edition. This book includes new chapters covering topics such as distributed PyTorch modeling, deploying PyTorch models in production, and developments around PyTorch with updated code. You'll start by...

Apress, 2019. — 184 p. — ISBN: 978-1484242575. Get up to speed with the deep learning concepts of Pytorch using a problem-solution approach. Starting with an introduction to PyTorch, you'll get familiarized with tensors, a type of data structure used to calculate arithmetic operations and also learn how they operate. You will then take a look at probability distributions using...

O’Reilly Media, Inc., 2021. — 310 p. — ISBN: 978-1-492-09000-7. This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips. Author Joe Papa provides instant access to syntax, design patterns, and code examples to accelerate your development and reduce the time you spend searching for answers....

O’Reilly Media, 2019. — 220 p. — ISBN: 978-1-492-04535-9. Take the next steps toward mastering deep learning, the machine learning method that’s transforming the world around us by the second. In this practical book, you’ll get up to speed on key ideas using Facebook’s open-source PyTorch framework and gain the latest skills you need to create your very own neural networks. Ian...

O’Reilly Media, 2019. — 256 p. — ISBN: 1491978236 From the Preface This book aims to bring newcomers to natural language processing (NLP) and deep learning to a tasting table covering important topics in both areas. Both of these subject areas are growing exponentially. As it introduces both deep learning and NLP with an emphasis on implementation, this book occupies an...

O’Reilly Media, 2019. — 256 p. Natural Language Processing (NLP) offers unbounded opportunities for solving interesting problems in artificial intelligence, making it the latest frontier for developing intelligent, deep learning-based applications. If you’re a developer or researcher ready to dive deeper into this rapidly growing area of artificial intelligence, this practical...

GitforGits, 2023. — 321 p. — ISBN-13 978-8196288372. This book is a comprehensive guide to understanding and utilizing PyTorch 2.0 for Deep Learning applications. It starts with an introduction to PyTorch, its various advantages over other Deep Learning frameworks, and its blend with CUDA for GPU acceleration. We delve into the heart of PyTorch – tensors, learning their...

2nd Edition. — GitforGits, 2024. — 314 p. — ISBN-13 978-8119177916. "Learning PyTorch 2.0, Second Edition" is a fast-learning, hands-on book that emphasizes practical PyTorch scripting and efficient model development using PyTorch 2.3 and CUDA 12. This edition is centered on practical applications and presents a concise methodology for attaining proficiency in the most recent...

Independently published, 2024. — 100 c. Dialogue systems are revolutionizing human-computer interaction, enabling us to interact with machines naturally and engagingly. But what about open-domain systems? These are the future, capable of extended conversations on any topic, just like you would with a friend. This book empowers you to conquer the world of Natural Language...

Packt Publishing, 2021. — 340 p. — ISBN: 978-1-80020-810-0. Harness the power of the easy-to-use, high-performance fastai framework to rapidly create complete deep learning solutions with few lines of code Key Features Discover how to apply state-of-the-art deep learning techniques to real-world problems Build and train neural networks using the power and flexibility of the...

Packt Publishing, 2022 — 56 p. — ISBN: 9781800561618. Build, train, deploy, and scale deep learning models quickly and accurately, improving your productivity using the lightweight PyTorch Wrapper PyTorch Lightning lets researchers build their Deep Learning (DL) models without having to worry about the boilerplate. With the help of this book, you'll be able to maximize...

Manning, 2020. — 488 p. — ISBN: 9781617295263. Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you, and...

Manning Publications, 2020. — 419 p. Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you — and your deep...

Manning, 2019. — vi, 134 p. — ISBN: 978-1-61729-712-0. This book is intended to be a starting point for software engineers, data scientists, and motivated students who are fluent in Python and want to become comfortable using PyTorch to build deep learning projects. To that end, we take a hands-on approach; we encourage you to keep your computer at the ready so that you can...

Manning Publications, 2020. — 520 p. — ISBN: 978-1617295263. Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with...

BPB Publications, 2024. — 412 p. — ISBN: 978-93-55517-494. Your key to transformer-based NLP is vision, speech, and multimodalities. Key Features Transformer architecture for different modalities and multimodalities. Practical guidelines to build and fine-tune transformer models. Comprehensive code samples with detailed documentation. Description This book covers transformer...

Leanpub, 2020. — 179 p. — ASIN B0895YQYFC. Learn how to solve real-world problems with Deep Learning models (NLP, Computer Vision, and Time Series). Go from prototyping to deployment with PyTorch and Python! PyTorch is the best Deep Learning library there (currently) is, period! Doing ML with PyTorch feels like a superpower (of course, there are bad parts, too). Trust me, I...

Independently published, 2023. — 48 p. — ASIN: B0CN4XBN73. Dive into the world of intelligent systems with 'Intro to Machine Learning with PyTorch.' This comprehensive ebook serves as your gateway to understanding the fundamentals of machine learning using PyTorch, a powerful open-source machine learning library. Whether you're a beginner or have some experience in the field,...