PyTorch

Independently published, 2024. — 540 р. — 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 intuitive...

Packt Publishing, 2020. — 452 p. — ISBN: 978-1-83864-483-3. Discover powerful ways to explore deep learning algorithms and solve real-world computer vision problems using Python Developers can gain a high-level understanding of digital images and videos using computer vision techniques. With this book, you’ll learn how to solve the trickiest of problems in computer vision (CV)...

Packt Publishing Ltd., 2020. — 276 p. — ISBN: 978-1-78980-274-0. Become a proficient NLP data scientist by developing deep learning models for NLP and extract valuable insights from structured and unstructured data In the internet age, where an increasing volume of text data is generated daily from social media and other platforms, being able to make sense of that data is a...

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 tools...

Independently published, 2024. — 288 p. — ASIN: B07N7KP6NJ. PyTorch: A Comprehensive Guide to Deep Learning for Beginners – A Step-by-Step Guide is designed to demystify the world of deep learning, making it accessible to individuals with little to no programming experience. It focuses on practical implementation using PyTorch, a popular and user-friendly framework. Why This...

Packt Publishing Ltd., 2020. — 448 p. —ISBN: 978-1-78953-051-3. Apply deep learning techniques and neural network methodologies to build, train, and optimize generative network models With continuously evolving research and development, Generative Adversarial Networks (GANs) are the next big thing in the field of deep learning. This book highlights the key improvements in GANs...

O’Reilly Media, Inc., 2020. — 624 p. — ISBN: 9781492045526. 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. — 160 p. — ASIN: B07N7KP6NJ. This 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...

Apress Media LLC, 2022. — 240 p. — ISBN-13: 978-1-4842-8273-1. 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...

Independently published, 2024. — 117 p. — ASIN: B0CSV4H1FD. Large Language Models (LLMs) are revolutionizing AI, understanding and generating human language like never before. But harnessing their full potential requires the right tools. This book takes you on a deep dive into pyTorch, the leading framework for building and optimizing LLMs. This book is your practical guide to...

Packt Publishing, 2019. — 441 p. — ISBN: 978-1-83855-196-4. Implement reinforcement learning techniques and algorithms with the help of real-world examples and recipes Reinforcement learning (RL) is a branch of machine learning that has gained popularity in recent times. It allows you to train AI models that learn from their own actions and optimize their behavior. PyTorch has...

Packt Publishing, 2020. — 338 p. — ISBN: 978-1-83855-704-1. Use PyTorch to build end-to-end artificial intelligence systems using Python Artificial Intelligence (AI) continues to grow in popularity and disrupt a wide range of domains, but it is a complex and daunting topic. In this book, you’ll get to grips with building deep learning apps, and how you can use PyTorch for...

Apress, 2019. — 184 p. — ISBN13: (electronic): 978-1-4842-4258-2. 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...

2nd Edition. — Apress Media, LLC, 2022. — 290 p. — 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...

2nd edition. — Packt Publishing Ltd., 2019. — 304 p. — ISBN: 978-1-83855-300-5. Build and train neural network models with high speed and flexibility in text, vision, and advanced analytics using PyTorch 1.x. Key Features Implement deep learning techniques to build neural network architectures using PyTorch 1.x; Understand GPU computing to perform heavy deep learning...

O’Reilly Media, 2019. — 210 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. — 250 p. — ISBN13: 978-1-491-97823-8. 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...

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...

GitforGits, October 5, 2023. — 238 p. — ISBN-13: 978-8119177967. Starting a PyTorch Developer and Deep Learning Engineer career? Check out this 'PyTorch Cookbook,' a comprehensive guide with essential recipes and solutions for PyTorch and the ecosystem. The book covers PyTorch deep learning development from beginner to expert in well-written chapters. The book simplifies neural...

Packt Publishing, 2019. — 230 p. — ISBN: 978-1-78980-459-1. Implement techniques such as image classification and natural language processing (NLP) by understanding the different neural network architectures Machine learning is rapidly becoming the most preferred way of solving data problems, thanks to the huge variety of mathematical algorithms that find patterns, which are...

2nd Edition. — Packt Publishing Ltd., 2020. — 330 p. — ISBN: 978-1-83898-921-7. 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...

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...

Packt Publishing, 2019. — 250 p. — ISBN: 978-1-78883-413-1. Hands-on projects cover all the key deep learning methods built step-by-step in PyTorch PyTorch Deep Learning Hands-On is a book for engineers who want a fast-paced guide to doing deep learning work with Pytorch. It is not an academic textbook and does not try to teach deep learning principles. The book will help you...

BPB Publications, 2024. — 310 р. — ISBN: 978-93-55517-494. Your key to transformer based NLP, 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...

Пер. с англ. И. Пальти. — СПб.: Питер, 2020. — 256 с.: ил. — (Бестселлеры O’Reilly). — ISBN: 978-5-4461-1241-8 (рус.), ISBN: 978-1491978238 (англ.). Обработка текстов на естественном языке (Natural Language Processing, NLP) — крайне важная задача в области искусственного интеллекта. Успешная реализация делает возможными такие продукты, как Alexa от Amazon и Google Translate....