Applied Analytics Learning Press (4 results)
- Softcover
Seller: California Books, Miami, FL, U.S.A.California Books
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US$ 28.00
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Condition: New.
- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
Contact seller5-star sellerCondition: New
US$ 31.25
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
- Print on Demand
Seller: preigu, Osnabrück, Germanypreigu
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US$ 59.97
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Taschenbuch. Condition: Neu. THE AI LANDSCAPE | A Field Guide to Machine Learning, Generative AI, and Human-Centered AI Design | Frank Seres | Taschenbuch | Englisch | 2026 | Applied Analytics Learning Press | EAN 9798234110503 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, m…ail[at]preigu[dot]de | Anbieter: preigu Print on Demand.
- Softcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
Contact seller5-star sellerCondition: New
US$ 71.63
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 lea…rning, 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.
