Generative AI for Business Analysts: A Comprehensive Guide

Vemula, Anand

  • 出版商: Independently Published
  • 出版日期: 2024-06-17
  • 售價: $1,210
  • 貴賓價: 9.5$1,150
  • 語言: 英文
  • 頁數: 104
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798328699723
  • ISBN-13: 9798328699723
  • 相關分類: 人工智慧
  • 海外代購書籍(需單獨結帳)

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商品描述

Generative AI for Business Analysts: A Comprehensive Guide" equips business analysts with essential knowledge and practical skills to leverage generative AI technologies effectively. From understanding foundational concepts to implementing advanced solutions, this book bridges the gap between AI theory and business application.

The book begins with an overview of generative AI, exploring key technologies such as GANs, VAEs, and Transformers, and their applications across various industries. Business analysts learn to identify suitable AI-driven solutions for enhancing operations, from content creation and data augmentation to predictive analysis and personalization.

An emphasis on practicality is woven throughout the guide. Readers delve into project planning and execution, learning to set objectives, allocate resources, and manage timelines effectively. Collaboration with data scientists and AI engineers is explored, ensuring seamless integration of AI solutions into existing business frameworks.

Tools and platforms crucial for AI implementation, including TensorFlow, PyTorch, and OpenAI, are detailed with pros and cons. Hands-on tutorials and case studies provide step-by-step guidance on building and deploying generative AI models, empowering analysts to apply their newfound skills in real-world scenarios.

Ethical considerations, privacy concerns, and regulatory compliance are addressed comprehensively, highlighting the importance of responsible AI deployment. Readers gain insights into identifying biases, mitigating risks, and adhering to data privacy laws such as GDPR and CCPA.

Measuring AI performance becomes actionable with metrics like accuracy, precision-recall, and specific metrics for generative models like Inception Score and FID. Practical workshops offer exercises in A/B testing, experimental design, and continuous monitoring to refine AI models and ensure ongoing success.

The future of generative AI and evolving roles for business analysts are explored, preparing readers for advancements in AI technologies and industry trends. Resources for further learning and career development conclude the guide, empowering analysts to stay current and thrive in the AI-driven landscape.

商品描述(中文翻譯)

《商業分析師的生成式 AI:全面指南》為商業分析師提供了必要的知識和實用技能,以有效利用生成式 AI 技術。從理解基礎概念到實施進階解決方案,本書彌合了 AI 理論與商業應用之間的鴻溝。

本書首先概述了生成式 AI,探討了 GAN、VAE 和 Transformers 等關鍵技術及其在各行各業的應用。商業分析師學會識別適合的 AI 驅動解決方案,以提升業務運作,涵蓋內容創建、數據增強、預測分析和個性化等方面。

本指南貫穿了實用性的重要性。讀者將深入了解專案規劃和執行,學習如何設定目標、分配資源和有效管理時間表。書中探討了與數據科學家和 AI 工程師的合作,確保 AI 解決方案能無縫整合到現有的商業框架中。

書中詳細介紹了 AI 實施所需的工具和平台,包括 TensorFlow、PyTorch 和 OpenAI,並分析其優缺點。實作教程和案例研究提供了逐步指導,幫助分析師在現實情境中應用他們新學到的技能。

倫理考量、隱私問題和法規遵循也得到了全面的探討,強調負責任的 AI 部署的重要性。讀者將獲得識別偏見、降低風險和遵守數據隱私法規(如 GDPR 和 CCPA)的見解。

衡量 AI 性能變得可行,使用準確度、精確率-召回率等指標,以及針對生成模型的特定指標,如 Inception Score 和 FID。實用的工作坊提供 A/B 測試、實驗設計和持續監控的練習,以精煉 AI 模型並確保持續成功。

本書探討了生成式 AI 的未來及商業分析師的演變角色,為讀者準備迎接 AI 技術和行業趨勢的進步。最後提供進一步學習和職業發展的資源,幫助分析師在 AI 驅動的環境中保持最新並蓬勃發展。