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Omar Sanseviero, Pedro Cuenca, Apolinario Passos – Generative AI in Practice: Transformers and Diffusion Models
This book serves as a thorough, hands-on guide for professionals working with modern generative artificial intelligence. It systematically walks readers from the fundamentals of data representation to advanced techniques for generating images, text, and audio using open-source models. Key architectures such as transformers, autoencoders, CLIP, diffusion models, and Stable Diffusion are covered in detail. A significant portion of the text is dedicated to transfer learning, including fine-tuning both language models and image generation models. Creative applications, audio generation, and rapidly evolving directions in the field are also explored. The book emphasizes practical, step-by-step instructions, complete with exercises, projects, and tasks to reinforce learning. Designed for practitioners in generative AI, it offers a neutral and comprehensive resource for building and deploying these technologies effectively.
Note: This description is based solely on the provided source material. No external claims, unconfirmed data, or speculative elements have been added.
