Mastering Generative AI with PyTorch: From Fundamentals to Advanced Models

Author:   Anand Vemula
Publisher:   Independently Published
ISBN:  

9798327167698


Pages:   78
Publication Date:   31 May 2024
Format:   Paperback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Mastering Generative AI with PyTorch: From Fundamentals to Advanced Models


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"**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."

Full Product Details

Author:   Anand Vemula
Publisher:   Independently Published
Imprint:   Independently Published
Dimensions:   Width: 15.20cm , Height: 0.40cm , Length: 22.90cm
Weight:   0.118kg
ISBN:  

9798327167698


Pages:   78
Publication Date:   31 May 2024
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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