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Condizione: good. The book is in good condition with all pages and cover intact, including the dust jacket if originally issued. The spine may show light wear. Pages may contain some notes or highlighting, and there might be a "From the library of" label. Boxed set packaging, shrink wrap, or included media like CDs may be missing.

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paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

Condizione: New.

Paperback. Condizione: New.

paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

Paperback. Condizione: new. Paperback. Mastering PyTorch: A Practical Guide to AI & Deep Learning Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

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Paperback. Condizione: new. Paperback. **Mastering Generative AI with PyTorch: From Fundamentals to Advanced Models** Unlock the potential of generative artificial intelligence with "Mastering Generative AI with PyTorch." This comprehensive guide takes you on a journey from the foundational concepts of generative AI to the implementation of advanced models, providing a clear and practical roadmap for mastering this cutting-edge technology. The book begins with an introduction to the core principles of generative AI, explaining its significance and applications in various fields such as art, entertainment, and scientific research. You will explore different types of generative models, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Autoregressive Models, gaining a deep understanding of their architectures and mechanisms. With a focus on hands-on learning, the book introduces you to PyTorch, one of the most popular and powerful deep learning frameworks. Step-by-step instructions guide you through the installation of PyTorch and fundamental operations, setting a strong foundation for building complex models. Each chapter is designed to build on the previous one, gradually increasing in complexity and depth. In the GANs section, you will learn about their architecture, training process, and advanced variations like Conditional GANs and CycleGANs. The book provides detailed code examples and explanations, enabling you to implement and train your own GANs for diverse applications. The VAE section delves into the mathematical foundations and training techniques of VAEs, including practical examples of implementing both standard and conditional VAEs with PyTorch. You'll gain insights into how VAEs can generate high-quality, realistic data and their use in creative and scientific tasks. Autoregressive models, including PixelCNN and PixelRNN, are thoroughly covered, with explanations of their applications in sequential data generation. The book also explores the integration of attention mechanisms and transformers to enhance model performance. By the end of this book, you will have a solid understanding of generative AI and be equipped with the skills to implement and experiment with various generative models using PyTorch. Whether you are a beginner or an experienced practitioner, "Mastering Generative AI with PyTorch" provides the knowledge and tools needed to excel in the exciting field of generative AI. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Condizione: good. A well-loved companion. Corners and cover might show a little wear, and you could find some notes or highlights. The dust jacket might be MIA, it might have been a library book and extras arenât guaranteedâ"but the storyâs all there!

Paperback. Condizione: New.

Condizione: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.

Paperback. Condizione: new. Paperback. DEEP LEARNING WITH PYTORCH: Master the Construction of Modern Neural Networks with Practicality and Efficiency - 2024 Edition, a comprehensive guide to elevate your artificial intelligence skills. Written by Diego Rodrigues, an international author with over 180 titles published in six languages, this book bridges the gap between theory and practice for creating innovative solutions with PyTorch, one of the most advanced deep learning libraries in the world.Whether you are a beginner or an experienced professional, this book provides a structured approach, from basics to advanced techniques, to apply Deep Learning efficiently and robustly. From tensor manipulation to the development of CNNs, RNNs, and Transformer architectures, you will find practical exercises and real-world applications that will help you solve modern-day problems.You will learn to: Build custom neural networks and implement them with PyTorch.Use advanced features such as distributed processing and GPU acceleration.Apply Deep Learning to computer vision, NLP, and other critical areas.Adopt best practices for data preprocessing, model validation, and optimization.The content includes applied case studies and practical examples optimized for cloud platforms like AWS and Google Cloud, offering a holistic view of implementing solutions with PyTorch.If you are ready to transform ideas into technological innovations, DEEP LEARNING WITH PYTORCH is the ultimate resource to shape the future with artificial intelligence. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback. Condizione: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Paperback. Condizione: Good. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.

Condizione: New.

Paperback. Condizione: new. Paperback. In today's fast-paced world of artificial intelligence and natural language processing, large language models (LLMs) have emerged as a groundbreaking technology, transforming industries and enabling new applications. "Mastering Large Language Models with PyTorch" is your essential guide to understanding, building, and deploying these powerful models using the popular PyTorch framework. This comprehensive book provides you with the knowledge and tools to harness the full potential of LLMs through hands-on tutorials and practical code examples.The book begins with an accessible introduction to LLMs, explaining their significance and diverse applications. From chatbots and sentiment analysis to text generation and summarization, you'll discover how LLMs are revolutionizing the way we interact with technology. The guide also covers why PyTorch has become the preferred choice for researchers and developers, highlighting its flexibility, ease of use, and robust community support.Getting started with PyTorch is made easy with step-by-step instructions on installation, environment setup, and basic operations. You'll quickly learn to navigate the PyTorch ecosystem and start experimenting with simple neural networks. As you progress, the book delves deeper into the intricacies of LLMs, explaining key concepts and terminology, and comparing popular architectures such as GPT, BERT, and T5.Data preparation is a critical aspect of training LLMs, and this guide covers best practices for collecting, cleaning, and preprocessing text data. You'll also learn to create efficient datasets and data loaders, ensuring smooth and fast training processes. The book provides a detailed walkthrough of building LLMs from scratch, covering model architecture, attention mechanisms, and transformer blocks, all illustrated with clear, annotated code examples.Training and fine-tuning LLMs are covered extensively, with practical advice on optimizing performance and leveraging pretrained models for specific tasks. You'll explore advanced topics like mixed precision training, distributed training, and model compression techniques, equipping you with the skills to handle large-scale data and deploy models effectively.Real-world case studies and success stories demonstrate the impact of LLMs across various domains, while troubleshooting tips and best practices help you overcome common challenges. The book also connects you to valuable community resources and support, ensuring you stay updated with the latest advancements.Whether you're a beginner or an experienced practitioner, "Mastering Large Language Models with PyTorch" is your go-to resource for mastering the art of LLMs and applying them to solve real-world problems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condizione: VeryGood. Cover/Case has some rubbing and edgewear. Access codes, CDs, slipcovers and other accessories may not be included.

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Condizione: Good. The cover and pages show normal wear. Paperback book. All items shipped Monday to Friday.

Condizione: New.