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Inference and Learning from Data: Volume 2: Inference
Ali H. Sayed你有多喜歡這本書?
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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 second volume, Inference, builds on the foundational topics established in volume I to introduce students to techniques for inferring unknown variables and quantities, including Bayesian inference, Monte Carlo Markov Chain methods, maximum-likelihood estimation, hidden Markov models, Bayesian networks, and reinforcement learning. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including solutions for instructors), 180 solved examples, almost 200 figures, datasets and downloadable Matlab code. Supported by sister volumes Foundations 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.
體積:
2
年:
2023
版本:
New
出版商:
Cambridge University Press
語言:
english
頁數:
1070
ISBN 10:
1009218263
ISBN 13:
9781009218269
文件:
PDF, 52.04 MB
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IPFS:
CID , CID Blake2b
english, 2023
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