A First Course in Machine Learning, 2/e (Hardcover)

Simon Rogers, Mark Girolami

  • 出版商: CRC
  • 出版日期: 2016-07-18
  • 售價: $3,150
  • 貴賓價: 9.5$2,993
  • 語言: 英文
  • 頁數: 427
  • 裝訂: Turtleback
  • ISBN: 1498738486
  • ISBN-13: 9781498738484
  • 相關分類: Machine Learning
  • 其他版本: A First Course in Machine Learning
  • 立即出貨 (庫存 < 3)

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商品描述

"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC."
―Devdatt Dubhashi, Professor, Department of Computer Science and Engineering, Chalmers University, Sweden

"This textbook manages to be easier to read than other comparable books in the subject while retaining all the rigorous treatment needed. The new chapters put it at the forefront of the field by covering topics that have become mainstream in machine learning over the last decade."
―Daniel Barbara, George Mason University, Fairfax, Virginia, USA

"The new edition of A First Course in Machine Learning by Rogers and Girolami is an excellent introduction to the use of statistical methods in machine learning. The book introduces concepts such as mathematical modeling, inference, and prediction, providing ‘just in time’ the essential background on linear algebra, calculus, and probability theory that the reader needs to understand these concepts."
―Daniel Ortiz-Arroyo, Associate Professor, Aalborg University Esbjerg, Denmark

"I was impressed by how closely the material aligns with the needs of an introductory course on machine learning, which is its greatest strength…Overall, this is a pragmatic and helpful book, which is well-aligned to the needs of an introductory course and one that I will be looking at for my own students in coming months."
―David Clifton, University of Oxford, UK

"The first edition of this book was already an excellent introductory text on machine learning for an advanced undergraduate or taught masters level course, or indeed for anybody who wants to learn about an interesting and important field of computer science. The additional chapters of advanced material on Gaussian process, MCMC and mixture modeling provide an ideal basis for practical projects, without disturbing the very clear and readable exposition of the basics contained in the first part of the book."
―Gavin Cawley, Senior Lecturer, School of Computing Sciences, University of East Anglia, UK

"This book could be used for junior/senior undergraduate students or first-year graduate students, as well as individuals who want to explore the field of machine learning…The book introduces not only the concepts but the underlying ideas on algorithm implementation from a critical thinking perspective."
―Guangzhi Qu, Oakland University, Rochester, Michigan, USA

商品描述(中文翻譯)

「A First Course in Machine Learning」是由Simon Rogers和Mark Girolami所著的機器學習入門書籍,目前是最好的入門書籍之一。它結合了嚴謹和精確性與易讀性,從貝葉斯分析的基礎細節解釋開始,並延伸到無限混合模型、高斯過程和馬可夫鏈蒙特卡羅等前沿主題。

「這本教科書在比較類似的主題書籍中更容易閱讀,同時保留了所有需要的嚴謹處理。新的章節使其成為領域的前沿,涵蓋了在過去十年中在機器學習中變得主流的主題。」

「Rogers和Girolami的《機器學習初級課程》新版是在機器學習中使用統計方法的優秀入門書籍。該書介紹了數學建模、推理和預測等概念,並提供了線性代數、微積分和概率論的基礎背景,讓讀者能夠理解這些概念。」

「我對這本書與機器學習入門課程的需求有多麼密切感到印象深刻,這是它最大的優勢...總的來說,這是一本實用且有幫助的書籍,非常適合入門課程的需求,我將在未來幾個月內為我的學生們參考。」

「這本書的第一版已經是一本優秀的機器學習入門教材,適用於高年級本科生或碩士課程,或者任何想要學習這個有趣且重要的計算機科學領域的人。關於高斯過程、馬可夫鏈蒙特卡羅和混合模型的附加章節為實際項目提供了理想的基礎,同時不擾亂書籍第一部分中清晰易讀的基礎內容。」

「這本書可以用於大學三年級/四年級本科生或研究生的第一年,以及想要探索機器學習領域的個人...該書不僅介紹了概念,還從批判性思維的角度介紹了算法實現的基本思想。」