Fundamentals of Pattern Recognition and Machine Learning

Braga-Neto, Ulisses

Fundamentals of Pattern Recognition and Machine Learning
  • 出版商: Springer
  • 出版日期: 2024-08-07
  • 售價: $2,940
  • 貴賓價: 9.5 折 $2,793
  • 語言: 英文
  • 頁數: 400
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031609492
  • ISBN-13: 9783031609497
  • 相關分類: Machine Learning

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

This book is a concise but thorough introduction to the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as deep neural networks and Gaussian process regression. The Second Edition includes a new chapter on the emerging topic of physics-informed machine learning and significant additions to the section on neural networks.

Combining theory and practice, this book is suitable for the graduate or advanced undergraduate level classroom and self-study. It fills the need of a mathematically-rigorous text that is relevant to the practitioner as well, with datasets from applications in bioinformatics and materials informatics used throughout to illustrate the theory. These datasets are available from the book website to be used in end-of-chapter coding assignments based on python and Keras/Tensorflow. All plots in the text were generated using python scripts and jupyter notebooks, which can be downloaded from the book website.

商品描述(中文翻譯)

本書是一本簡明而全面的介紹，涵蓋了在模式識別和機器學習中常用的工具，包括分類、降維、回歸和聚類，以及最近流行的主題，如深度神經網絡和高斯過程回歸。第二版新增了一章關於物理知識驅動的機器學習的前沿主題，並對神經網絡部分進行了重要的補充。

本書結合了理論與實踐，適合研究生或高年級本科生的課堂學習和自學。它滿足了對數學嚴謹的文本的需求，並且與實務工作者相關，書中使用了來自生物信息學和材料信息學的數據集來說明理論。這些數據集可從書籍網站獲得，用於基於 Python 和 Keras/Tensorflow 的章節結尾編碼作業。文中的所有圖表均使用 Python 腳本和 Jupyter notebooks 生成，這些也可以從書籍網站下載。

作者簡介

Ulisses Braga-Neto, Ph.D. is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University. His main research areas are pattern recognition, machine learning, statistical signal processing, and applications in bioinformatics and materials informatics. He has worked extensively in the field of error estimation for pattern recognition and machine learning, having received an NSF CAREER award for research in this area, and co-authored a monograph with Edward R. Dougherty on the topic. He has also made contributions to the field of Mathematical morphology in signal and image processing.

作者簡介(中文翻譯)

Ulisses Braga-Neto, Ph.D. 是德州農工大學電機與計算機工程系的教授。他的主要研究領域包括模式識別、機器學習、統計信號處理，以及在生物資訊學和材料資訊學中的應用。他在模式識別和機器學習的誤差估計領域有廣泛的研究，並因在該領域的研究獲得了 NSF CAREER 獎，並與 Edward R. Dougherty 共同撰寫了一本專著。他也對信號和影像處理中的數學形態學領域做出了貢獻。

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