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Synopsis
This book serves as an essential practitioner's guide to the world of recommender algorithms as it stands in early 2026. We begin with the indispensable baselines-from classic neighborhood models to powerful matrix factorization-and build toward the sophisticated deep learning architectures that power today's largest platforms, including hybrids for CTR prediction and state-of-the-art sequential models.
A core theme of this guide is the practical integration of the latest technological breakthroughs. We dedicate significant attention to the transformative impact of Large Language Models (LLMs), offering architectural blueprints for leveraging them as powerful semantic feature extractors, building reliable Retrieval-Augmented Generation (RAG) pipelines, and designing the next wave of generative and conversational recommender agents. Furthermore, we explore the critical role of multimodal models like CLIP for solving visual cold-start problems and provide insights into specialized areas like debiasing and fairness. This is more than a survey; it is a toolkit for the modern engineer. Each section balances conceptual depth with pragmatic advice on implementation, scalability, and production readiness, making it the definitive resource for professionals tasked with creating value through personalization."synopsis" may belong to another edition of this title.
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Recommender Algorithms
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Recommender Algorithms
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Recommender Algorithms
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Recommender Algorithms (Paperback)
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Paperback. Condition: new. Paperback. This book serves as an essential practitioner's guide to the world of recommender algorithms as it stands in early 2026. We begin with the indispensable baselines-from classic neighborhood models to powerful matrix factorization-and build toward the sophisticated deep learning architectures that power today's largest platforms, including hybrids for CTR prediction and state-of-the-art sequential models. A core theme of this guide is the practical integration of the latest technological breakthroughs. We dedicate significant attention to the transformative impact of Large Language Models (LLMs), offering architectural blueprints for leveraging them as powerful semantic feature extractors, building reliable Retrieval-Augmented Generation (RAG) pipelines, and designing the next wave of generative and conversational recommender agents. Furthermore, we explore the critical role of multimodal models like CLIP for solving visual cold-start problems and provide insights into specialized areas like debiasing and fairness. This is more than a survey; it is a toolkit for the modern engineer. Each section balances conceptual depth with pragmatic advice on implementation, scalability, and production readiness, making it the definitive resource for professionals tasked with creating value through personalization. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798232638405
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Recommender Algorithms
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Taschenbuch. Condition: Neu. Recommender Algorithms | Rauf Aliev | Taschenbuch | Englisch | 2025 | Rauf Aliev | EAN 9798232638405 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 134116566
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