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Paperback. Zustand: new. Paperback. Complete mathematical descrption of historical Artificial Intelligence (AI) models proceeding to comtemporary Models. The books initiates with simple and ingenous algorythms to advanced mathematical models that are the structure of advanced AI models. This item is printed on demand. Shipping m…ay be from multiple locations in the US or from the UK, depending on stock availability.
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Paperback. Zustand: new. Paperback. Complete mathematical descrption of historical Artificial Intelligence (AI) models proceeding to comtemporary Models. The books initiates with simple and ingenous algorythms to advanced mathematical models that are the structure of advanced AI models. This item is printed on demand. Shipping m…ay be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Paperback. Zustand: new. Paperback. This volume is one part of a planned five-volume treatise on machine learning in the age of artificialintelligence. It has been separated from the former collected first volume so that the reader may work througha more reasonable physical and intellectual unit without losing the order of the o…riginal argument.The division has not been made by accident of page count alone. A treatise should be cut where the joints areanatomical, not where the printer grows weary. The first new volume establishes orientation, data, mathematical foundations, and the first classical models. The second carries the classical arc into ensembles, kernels, unsupervised methods, evaluation, and the first great architectures of deep learning. The latervolumes of the complete series are reserved for foundation models, agents, multimodal systems, governance, domain practice, capstones, appendices, and professional reference.The style remains deliberately discursive. A manual gives steps; a treatise gives reasons. Equations appearwhen needed, and variables are introduced rather than lowered from a cloud with a small thunderclap. AIassistants are treated as useful instruments under judgement, not as substitutes for the grammar of evidence.The present volume contains Chapters 1-19. Its purpose is to preserve the original sequence while allowingthis part of the work to stand independently on the desk, in the hand, and in the mind.The reader will find chapter presentation pages before each chapter, formal notation where the argumentrequires it, worked examples, exercises with resolutions, references, and the sustained insistence that data, models, metrics, and deployment are not separate provinces but a single disciplined chain.The page numbers in the table below refer to the body of this new volume. Front matter is intentionallyunnumbered. Numbering begins with the presentation page of the first chapter in this part and continuesthrough the conclusion and index. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Paperback. Zustand: new. Paperback. For fifty years software obeyed a simple compact: the same input returned the same output. Then the machine learned to answer back, and a discipline built on predictability found that its ground had moved. Software AI Engineering is a complete account of what comes next - the engineering, alig…nment, governance, deployment, and philosophy of artificial-intelligence systems - and it makes that account, by deliberate design, without a single line of code.Its argument is that the hardest decisions in artificial intelligence are not made at the keyboard at all, but in the prior questions of what ought to be built, how its behaviour shall be judged, who answers for it when it errs, and whether, all things weighed, it should exist. Across fifteen parts and sixty-seven chapters the book carries the reader from the foundations of the new discipline through AI product engineering, system architecture, evaluation and testing, MLOps and LLMOps delivery, safety and abuse resistance, and the governance regimes now taking shape under the NIST framework and the EU AI Act, into the domains where AI meets medicine, law, and finance, and at last into the philosophy that was implicit all along.It is written for the people who must actually answer for these systems - engineers and product managers, founders and executives, board members, regulators, clinicians, and the thoughtful citizen - and it equips each with the questions to ask before a model is trusted to act in the world. Rigorous where it must be and ironic where it can afford to be, it treats responsible AI not as a compliance afterthought but as the very substance of the craft.A reference, an argument, and an education in judgement, for an age in which the capacity to direct intelligent systems matters more than the capacity to write their code. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Paperback. Zustand: new. Paperback. This is a strong, publishable Book for a niche but growing audience, with notable strengths in depth and structure, tempered by stylistic and market risks. Volume I (foundations through human factors, Chapters 1-53) stands well on its own as promised, while setting up the series. It feels like… a deliberate attempt at a "classic" treatise in the vein of older engineering texts (e.g., Brooks' Mythical Man-Month or Knuth's works), updated for the agentic AI era.StrengthsTimely and Substantive Contribution: Agentic coding (tools like Claude Code that go beyond autocomplete to read/edit/run code in a loop) is a real 2025-2026 shift. Anthropic's own reports and developer discussions confirm the move toward supervision, verification, context management, multi-agent orchestration, and calibrated trust-exactly the book's core thesis. The emphasis on verification as the new center of gravity, reversibility, and human judgment over fluency is insightful and practical. It avoids hype in favor of disciplined realism, which is refreshing and valuable.Rigorous Structure: Consistent chapter format (prose argument + quantitative thread + worked example + exercises with solutions) is excellent for a practitioner book. The delegation model (geometric distribution for attempts, speed-up S(p), overheads) in Chapter 1 is a highlight-simple, derivable math that grounds the philosophy. TOC shows comprehensive coverage: from basics to advanced engineering, languages, security, multi-agent, and psychology.Depth and Original Framing: It treats the tool as a "junior colleague" requiring supervision rather than magic. Sections on mental models, .claude config, skills/workflows, permission modes, and reviewing AI code fill a gap between shallow "prompting guides" and raw docs. The literary/historical tone (genealogy of tools, control loops as contractions) adds gravitas.Production Quality: Clean typesetting (EB Garamond), professional front matter, disclaimers, and ISSN. It positions itself as independent scholarship, which is smart given trademark sensitivities. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
