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....
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...
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...
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...
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...
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...
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...
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...
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, 2024. — 746 p. 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 PyTorch. All the code files are available...
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...
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...
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...
BPB Publications, 2024. — 310 p. — 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...
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...
Independently published, 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), period! Doing ML with PyTorch feels like a superpower (of course, there are bad parts, too)....