ISBN: 9798186224181 - machine learning in the age of artificial intelligence volume i: a comprehensive treatise from first principles to professional practice (6 resultados)

Taschenbuch. Condición: Neu. Neuware.

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Paperback. Condición: 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 original 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 multiple locations in the US or from the UK, depending on stock availability.…

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condición: 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 original 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.…