PyTorch

O’Reilly Media, Inc., 2021. — 310 p. — ISBN 978-1-492-09000-7. 2021-05-11: First Release Code Files Only! 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...

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 computer...

Packt Publishing, 2020. — 647 p. — ISBN 1839213477, 9781839213472. Packed with hands-on implementations of deep learning techniques to build image processing applications using PyTorch. Each chapter is accompanied by a GitHub folder with code notebooks and questions to cement your understanding. Key Features - Implement solutions to 50 real-world computer vision applications...

Packt Publishing Ltd., 2020. — 276 p. — ISBN: 978-1-78980-274-0. Code files only! 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...

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

Manning Publications, 2020. — 520 p. — ISBN: 978-1617295263. Code files only! 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...

Packt Publishing, 2020. — 355 p. — ISBN: 978-1-83864-483-3. Code files only! 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...

Packt Publishing, 2019. — 250 p. — ISBN: 978-1-78883-413-1. Code files only! 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...

Packt Publishing Ltd., 2020. — 301 p. —ISBN: 978-1-78953-051-3. Code files only! 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...

Packt, 2019. — 254 p. — ISBN: 978-1789804591. Code files Implement techniques such as image classification and natural language processing (NLP) by understanding the different neural network architectures Key Features Understand deep learning and how it can solve complex real-world problems Apply deep learning for image classification and text processing using neural networks...

Packt Publishing, 2018. — 262 p. Build neural network models in text, vision and advanced analytics using PyTorch Deep learning powers the most intelligent systems in the world, such as Google Voice, Siri, and Alexa. Advancements in powerful hardware, such as GPUs, software frameworks such as PyTorch, Keras, Tensorflow, and CNTK along with the availability of big data have made it...