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Recommender Algorithms

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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 brea...