Inference and Learning from Data: Volume 1 - Foundations (Hardcover, New Ed)

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. This first volume, Foundations, introduces core topics in inference and learning, such as matrix theory, linear algebra, random variables, convex optimization and stochastic optimization, and prepares students for studying their practical application in later volumes. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 600 end-of-chapter problems (including solutions for instructors), 100 figures, 180 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Inference and Learning, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, statistical analysis, data science and inference.

General

Imprint:	Cambridge UniversityPress
Country of origin:	United Kingdom
Release date:	December 2022
Authors:	Ali H. Sayed
Dimensions:	255 x 180 x 40mm (L x W x T)
Format:	Hardcover
Pages:	1010
Edition:	New Ed
ISBN-13:	978-1-00-921812-2
Categories:	Books > Computing & IT > Applications of computing > Signal processing Books > Computing & IT > Applications of computing > Pattern recognition Books > Reference & Interdisciplinary > Communication studies > Information theory > General Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Promotions
LSN:	1-00-921812-3
Barcode:	9781009218122

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