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Inference and Learning from Data

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Authors

, École Polytechnique Fédérale de Lausanne
Published 2022

Description

This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. The first volume, Foundations, establishes core topics in inference and learning, and prepares readers for studying their practical application. The second volume, Inference, introduces readers to cutting-edge techniques for inferring unknown variables and quantities. The final volume, Learning, provides a…

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Key features

  • Unique in its scale and depth, this is a comprehensive introduction to methods in data-driven learning and inference
  • Over 1280 end-of-chapter problems (with complete solutions for instructors), 600 figures and 470 in-text solved examples
  • A phenomenal contribution by a world authority in the field
  • Covers sufficient topics across the volumes for the construction of a variety of courses covering a wide range of themes