Machine Learning: A Probabilistic Perspective

Kevin P. Murphy

  • 出版商: MIT
  • 出版日期: 2012-08-24
  • 售價: $3,850
  • 貴賓價: 9.5$3,658
  • 語言: 英文
  • 頁數: 1104
  • 裝訂: Hardcover
  • ISBN: 0262018020
  • ISBN-13: 9780262018029
  • 相關分類: Machine Learning
  • 立即出貨(限量) (庫存=1)

買這商品的人也買了...

商品描述

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package--PMTK (probabilistic modeling toolkit)--that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

商品描述(中文翻譯)

現今網路資料的洪流需要自動化的資料分析方法。機器學習提供了這些方法,能夠自動偵測資料中的模式,並利用這些發現的模式來預測未來的資料。本教科書提供了一個全面且自成一體的機器學習領域介紹,基於統一的概率方法。內容涵蓋廣度和深度,提供了必要的背景知識,如概率、優化和線性代數,以及對該領域的最新發展的討論,包括條件隨機場、L1 正則化和深度學習。本書以非正式、易於理解的風格撰寫,並附有最重要算法的偽代碼。所有主題都以彩色圖像和從生物學、文本處理、計算機視覺和機器人學等應用領域中提取的實例進行豐富的說明。本書強調基於原則的模型化方法,而不是提供不同啟發式方法的食譜,通常使用圖形模型的語言以簡潔直觀的方式來指定模型。幾乎所有描述的模型都已在一個名為PMTK(概率建模工具包)的MATLAB軟件包中實現,該軟件包可在線上免費使用。本書適合具有初級大學數學背景的高年級本科生和初級研究生閱讀。