Foundations of Data Science (Hardcover)

Blum, Avrim, Hopcroft, John, Kannan, Ravi

  • 出版商: Cambridge
  • 出版日期: 2020-01-23
  • 售價: $1,200
  • 貴賓價: 9.8$1,176
  • 語言: 英文
  • 頁數: 432
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1108485065
  • ISBN-13: 9781108485067
  • 相關分類: Data Science
  • 立即出貨(限量) (庫存=1)

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商品描述

This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.

商品描述(中文翻譯)

本書介紹了數據科學的數學和算法基礎,包括機器學習、高維幾何和大型網絡分析。主題包括高維數據的反直覺性質,重要的線性代數技巧,如奇異值分解,隨機遊走和馬爾可夫鏈理論,機器學習的基礎和重要算法,以及聚類的算法和分析,大型網絡的概率模型,包括主題建模和非負矩陣分解,小波和壓縮感知。還介紹了重要的概率技巧,包括大數定律,尾部不等式,隨機投影的分析,機器學習的泛化保證,以及用於分析大型隨機圖的瞬態方法。此外,還討論了重要的結構和複雜度度量,如矩陣範數和VC維度。本書適用於設計和分析數據算法的本科和研究生課程。