The AI Landscape (Paperback)
Language: English
Published by Applied Analytics Learning Press, 2026
- Softcover
- New

Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
AbeBooks seller since October 12, 2005
Condition: New
US$ 32.20
Quantity: 1 available
Add to basketItem description from seller
Paperback. This book gives professionals, students, educators, managers, analysts, entrepreneurs, and curious readers a clear map of modern AI in applied, easy-to-follow language. It explains how the major pieces fit together, including machine learning, deep learning, generative AI, prompt engineering, retrieval-augmented generation (RAG), generative adversarial networks (GANs), AI agents, human-centered design, model evaluation, risk, and business value.Rather than treating AI as a single technology, this guide shows AI as a landscape of connected ideas, tools, decisions, and tradeoffs. You will learn how models are trained, how prompts shape outputs, how retrieval can ground answers in documents, how agents use tools and workflows, how synthetic media is created, and how to evaluate whether an AI system is accurate, useful, safe, and worth the cost.Inside, you will learn how to think about: - Machine learning, deep learning, RAG, GANs, and generative AI- Prompts, tokens, delimiters, retrieval, guardrails, and AI agents- Human oversight, explainability, privacy, bias, and risk- Accuracy, false positives, false negatives, and model evaluation- Data quality, workflows, cost, ROI, and business value- Human-centered AI design and practical product decisions- When to use AI-and when a simpler solution is betterThe book uses diagrams, tables, examples, checklists, code-oriented illustrations, and field-guide explanations to make complex AI concepts easier to compare, remember, and apply. It is designed to help readers build a working mental model, not just memorize definitions.Use this guide if you are evaluating AI tools, teaching AI basics, planning an AI initiative, supporting technical teams, designing an AI-powered product, or exploring an entrepreneurial AI idea. It will help you ask better questions, recognize common failure modes, understand tradeoffs, and communicate more clearly with both technical and nontechnical audiences. A practical field guide to machine learning, generative AI, RAG, AI agents, human-centered design, risk, evaluation, and business value. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …
Seller Inventory # 9798234110503
- Title
- The AI Landscape (Paperback)
- Author
- Frank Seres
- Publisher
- Applied Analytics Learning Press
- Publication year
- 2026
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 13
- 9798234110503
This book gives professionals, students, educators, managers, analysts, entrepreneurs, and curious readers a clear map of modern AI in applied, easy-to-follow language. It explains how the major pieces fit together, including machine learning, deep learning, generative AI, prompt engineering, retrieval-augmented generation (RAG), generative adversarial networks (GANs), AI agents, human-centered design, model evaluation, risk, and business value.
Rather than treating AI as a single technology, this guide shows AI as a landscape of connected ideas, tools, decisions, and tradeoffs. You will learn how models are trained, how prompts shape outputs, how retrieval can ground answers in documents, how agents use tools and workflows, how synthetic media is created, and how to evaluate whether an AI system is accurate, useful, safe, and worth the cost.
Inside, you will learn how to think about:
• Machine learning, deep learning, RAG, GANs, and generative AI
• Prompts, tokens, delimiters, retrieval, guardrails, and AI agents
• Human oversight, explainability, privacy, bias, and risk
• Accuracy, false positives, false negatives, and model evaluation
• Data quality, workflows, cost, ROI, and business value
• Human-centered AI design and practical product decisions
• When to use AI—and when a simpler solution is better
The book uses diagrams, tables, examples, checklists, code-oriented illustrations, and field-guide explanations to make complex AI concepts easier to compare, remember, and apply. It is designed to help readers build a working mental model, not just memorize definitions.
Use this guide if you are evaluating AI tools, teaching AI basics, planning an AI initiative, supporting technical teams, designing an AI-powered product, or exploring an entrepreneurial AI idea. It will help you ask better questions, recognize common failure modes, understand tradeoffs, and communicate more clearly with both technical and nontechnical audiences.
"Synopsis" may belong to another edition of this title.
Grand Eagle Retail
Bensenville, IL, U.S.A.
AbeBooks seller since October 12, 2005
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