Generative AI in Theory: Practical Applications and Concepts

Vemula, Anand

  • 出版商: Independently Published
  • 出版日期: 2024-06-18
  • 售價: $1,120
  • 貴賓價: 9.5$1,064
  • 語言: 英文
  • 頁數: 66
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798328791519
  • ISBN-13: 9798328791519
  • 相關分類: 人工智慧
  • 海外代購書籍(需單獨結帳)

商品描述

Generative AI in Theory: Practical Applications and Concepts" delves into the fundamentals and applications of generative artificial intelligence (AI), offering a comprehensive exploration suitable for both beginners and seasoned professionals. This book is a definitive guide that demystifies complex AI techniques and showcases their practical implementations across various domains.

Starting with foundational concepts, the book covers essential topics such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Autoregressive Models. Readers will gain insights into how these models generate new data instances, create realistic images, and even compose music. The theoretical underpinnings are explained with clarity, accompanied by hands-on examples and tutorials using popular frameworks like TensorFlow and PyTorch.

Moving to advanced topics, the book explores Energy-Based Models including Boltzmann Machines and Contrastive Divergence, providing practical insights into their applications in recommendation systems and anomaly detection. Neural Ordinary Differential Equations are introduced as a powerful tool for continuous-time sequence modeling, offering real-world applications in time-series forecasting and simulations.

Flow-Based Models like Normalizing Flows and Diffusion Models are detailed for their capabilities in high-quality image generation and text completion tasks. Case studies in natural language processing, computer vision, and audio generation illustrate how these techniques are transforming industries.

The ethical and societal implications of generative AI are carefully examined, addressing concerns such as bias, privacy, and economic impacts. The book concludes with a forward-looking perspective on emerging trends and unresolved challenges, preparing readers for the future of AI innovation.

"Generative AI in Theory" is an essential resource for AI enthusiasts, researchers, and practitioners seeking a deeper understanding of cutting-edge AI technologies and their practical applications across diverse fields.

商品描述(中文翻譯)

《生成式人工智慧理論:實用應用與概念》深入探討生成式人工智慧(AI)的基本原理和應用,提供適合初學者和資深專業人士的全面探索。本書是一本權威指南,揭開複雜的AI技術面紗,展示其在各個領域的實際應用。

本書從基礎概念開始,涵蓋生成對抗網絡(GANs)、變分自編碼器(VAEs)和自回歸模型等重要主題。讀者將深入了解這些模型如何生成新的數據實例、創建逼真的圖像,甚至作曲。理論基礎以清晰的方式解釋,並附有使用流行框架如TensorFlow和PyTorch的實作範例和教程。

進入進階主題,本書探討基於能量的模型,包括玻爾茲曼機和對比散度,提供其在推薦系統和異常檢測中的應用實用見解。神經常微分方程被介紹為一種強大的工具,用於連續時間序列建模,並在時間序列預測和模擬中提供實際應用。

流基模型如正規化流和擴散模型被詳細介紹,展示其在高品質圖像生成和文本補全任務中的能力。自然語言處理、計算機視覺和音頻生成的案例研究說明了這些技術如何改變行業。

本書仔細檢視生成式AI的倫理和社會影響,探討偏見、隱私和經濟影響等問題。最後,本書以前瞻性的視角總結新興趨勢和未解決的挑戰,為讀者準備迎接AI創新的未來。

《生成式人工智慧理論》是AI愛好者、研究人員和實務工作者尋求深入了解尖端AI技術及其在各個領域實際應用的必備資源。