Generative AI Journal: Comprehensive Guide and Practical Solutions

Vemula, Anand

  • 出版商: Independently Published
  • 出版日期: 2024-06-22
  • 售價: $830
  • 貴賓價: 9.5$789
  • 語言: 英文
  • 頁數: 90
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798329141009
  • ISBN-13: 9798329141009
  • 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 Journal: Comprehensive Guide and Practical Solutions is an in-depth exploration of generative artificial intelligence, designed to equip readers with both theoretical knowledge and practical skills. This book is structured to cater to a diverse audience, from AI enthusiasts and researchers to professionals seeking to apply generative AI in real-world scenarios.

The journey begins with an introduction to generative AI, explaining what it is, its historical evolution, and the fundamental concepts and terminologies essential to understanding the field. It then delves into the importance and impact of generative AI across various industries, highlighting its transformative potential.

The foundation of generative AI is laid out through a detailed examination of machine learning basics, deep learning fundamentals, and neural network overviews. Key generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) are thoroughly explained, including their architectures, types, and practical applications.

The book explores advanced topics such as transfer learning, reinforcement learning in generative AI, data augmentation, and zero-shot and few-shot learning, providing readers with cutting-edge techniques to enhance their generative models. Ethical considerations, including deepfakes, bias, fairness, and privacy concerns, are addressed to ensure responsible AI practices.

Practical implementations are a core focus, with hands-on tutorials using popular tools and libraries like TensorFlow and PyTorch. Readers will learn how to build, train, optimize, deploy, and scale generative models. Detailed case studies, including GANs in art creation, VAEs in medical imaging, and text generation for content creation, illustrate the real-world impact and versatility of generative AI.

Looking towards the future, the book discusses emerging trends, potential applications, and research frontiers in generative AI, offering insights into the evolving landscape and its implications.

Generative AI Journal: Comprehensive Guide and Practical Solutions is an essential resource for anyone looking to master the art and science of generative AI, blending theoretical foundations with practical insights and applications.

商品描述(中文翻譯)

《生成式人工智慧期刊:全面指南與實用解決方案》是對生成式人工智慧的深入探索,旨在為讀者提供理論知識和實用技能。本書的結構設計適合多元的讀者群,從人工智慧愛好者和研究人員到尋求在現實場景中應用生成式人工智慧的專業人士。

這段旅程始於對生成式人工智慧的介紹,解釋其定義、歷史演變以及理解該領域所需的基本概念和術語。接著深入探討生成式人工智慧在各行各業中的重要性和影響,突顯其變革潛力。

生成式人工智慧的基礎通過對機器學習基礎、深度學習基本原理和神經網絡概述的詳細檢視而建立。關鍵的生成模型,如生成對抗網絡(GANs)和變分自編碼器(VAEs),將被徹底解釋,包括其架構、類型和實際應用。

本書探討了進階主題,如轉移學習、生成式人工智慧中的強化學習、數據增強,以及零樣本和少樣本學習,為讀者提供提升其生成模型的尖端技術。倫理考量,包括深偽技術、偏見、公平性和隱私問題,亦被納入討論,以確保負責任的人工智慧實踐。

實際實施是本書的核心重點,提供使用流行工具和庫(如 TensorFlow 和 PyTorch)的實作教程。讀者將學習如何構建、訓練、優化、部署和擴展生成模型。詳細的案例研究,包括 GANs 在藝術創作中的應用、VAEs 在醫學影像中的應用,以及文本生成在內容創作中的應用,展示了生成式人工智慧的實際影響和多樣性。

展望未來,本書討論了生成式人工智慧中的新興趨勢、潛在應用和研究前沿,提供對不斷演變的領域及其影響的見解。

《生成式人工智慧期刊:全面指南與實用解決方案》是任何希望掌握生成式人工智慧藝術與科學的人的重要資源,將理論基礎與實用見解和應用相結合。